CN102999911B

CN102999911B - Three-dimensional image quality objective evaluation method based on energy diagrams

Info

Publication number: CN102999911B
Application number: CN201210493072.5A
Authority: CN
Inventors: 邵枫; 顾珊波; 蒋刚毅; 郁梅; 李福翠
Original assignee: Ningbo University
Current assignee: Ningbo University
Priority date: 2012-11-27
Filing date: 2012-11-27
Publication date: 2015-06-03
Anticipated expiration: 2032-11-27
Also published as: CN102999911A

Abstract

The invention discloses a three-dimensional image quality objective evaluation method based on energy diagrams. The three-dimensional image quality objective evaluation method includes: firstly respectively calculating energy diagrams on different scales and directions of original undistorted three-dimensional images and energy diagrams on different scales and directions of fuzzy three-dimensional images to be evaluated to obtain the objective evaluation metrics of each pixel point of the fuzzy three-dimensional images to be evaluated, and then performing fusion on the objective evaluation metrics of each pixel point of the fuzzy three-dimensional images to be evaluated according to the energy diagrams and binocular minimum perceptible changing images to obtain image quality objective evaluation predicted values of the fuzzy three-dimensional images to be evaluated. The three-dimensional image quality objective evaluation method has the advantages of being capable of well reflecting visual perception characteristics of human visual systems by obtaining the energy diagrams of different scales and directions, performing fusion on the energy diagrams and the minimum perceptible changing images, and being capable of effectively improving objective evaluation results and correlation of subjective perception.

Description

Stereo image quality objective evaluation method based on energy diagram

Technical Field

The invention relates to an image quality evaluation method, in particular to a three-dimensional image quality objective evaluation method based on an energy map.

Background

With the rapid development of image coding technology and stereoscopic display technology, the stereoscopic image technology has received more and more extensive attention and application, and has become a current research hotspot. The stereo image technology utilizes the binocular parallax principle of human eyes, the left and right viewpoint images from the same scene are respectively and independently received by binoculars, and binocular parallax is formed through brain fusion, so that the stereo image with depth feeling and reality feeling is appreciated. Because of the influence of the acquisition system and the storage compression and transmission equipment, a series of distortions are inevitably introduced into the stereo image, and compared with a single-channel image, the stereo image needs to ensure the image quality of two channels simultaneously, so that the quality evaluation of the stereo image has very important significance. However, currently, an effective objective evaluation method for evaluating the quality of a stereoscopic image is lacking. Therefore, establishing an effective objective evaluation model of the quality of the stereo image has very important significance.

At present, a plane image quality evaluation method is generally directly applied to evaluating stereoscopic image quality, however, a process of fusing left and right viewpoint images of a stereoscopic image to generate a stereoscopic effect is not a simple process of superimposing the left and right viewpoint images and is difficult to express by a simple mathematical method, so that how to extract effective characteristic information from the stereoscopic image to simulate binocular stereoscopic fusion, how to modulate an objective evaluation result according to a visual masking characteristic of human eyes and a response characteristic of binocular energy intensity of the human eyes, so that the objective evaluation result is more perceptually accordant with a human visual system, and the problem needs to be researched and solved in the process of objectively evaluating the stereoscopic image quality.

Disclosure of Invention

The invention aims to provide an objective evaluation method for the quality of a three-dimensional image based on an energy map, which can effectively improve the correlation between objective evaluation results and subjective perception.

The technical scheme adopted by the invention for solving the technical problems is as follows: a three-dimensional image quality objective evaluation method based on an energy map is characterized in that the processing process is as follows: firstly, acquiring an energy diagram of the original undistorted stereo image in different scales and directions according to even symmetric frequency response and odd symmetric frequency response of each pixel point in the left viewpoint image and the right viewpoint image of the original undistorted stereo image in different scales and directions and a pixel value of each pixel point in a parallax image between the left viewpoint image and the right viewpoint image of the original undistorted stereo image, acquiring energy graphs of the distorted stereo image to be evaluated in different scales and directions according to even symmetric frequency response and odd symmetric frequency response of each pixel point in the left viewpoint image and the right viewpoint image of the distorted stereo image to be evaluated in different scales and directions and pixel values of each pixel point in a parallax image between the left viewpoint image and the right viewpoint image of the original undistorted stereo image; then obtaining an objective evaluation metric value of each pixel point in the distorted stereo image to be evaluated according to the two energy maps; obtaining an objective evaluation metric value of the distorted three-dimensional image to be evaluated for reflecting a binocular visual masking effect according to the objective evaluation metric value of each pixel point in the distorted three-dimensional image to be evaluated and the binocular minimum perceptible change image of the left viewpoint image of the distorted three-dimensional image to be evaluated, and obtaining an objective evaluation metric value of the distorted three-dimensional image to be evaluated for reflecting binocular energy intensity according to the objective evaluation metric value of each pixel point in the distorted three-dimensional image to be evaluated and energy maps of the distorted three-dimensional image to be evaluated in different scales and directions; and finally, fusing an objective evaluation metric value for reflecting binocular visual masking effect and an objective evaluation metric value for reflecting binocular energy intensity of the distorted three-dimensional image to be evaluated to obtain an objective evaluation prediction value of the image quality of the distorted three-dimensional image to be evaluated.

The method specifically comprises the following steps:

making S_orgFor original undistorted stereo image, let S_disFor the distorted stereo image to be evaluated, S_orgIs noted as { L_org(x, y) }, adding S_orgIs noted as { R_org(x, y) }, adding S_disIs noted as { L_dis(x, y) }, adding S_disIs noted as { R_dis(x, y) }, wherein (x, y) denotes a coordinate position of a pixel point in the left viewpoint image and the right viewpoint image, x is 1. ltoreq. x.ltoreq.W, y is 1. ltoreq. y.ltoreq.H, W denotes a width of the left viewpoint image and the right viewpoint image, H denotes a height of the left viewpoint image and the right viewpoint image, L is L_org(x, y) represents { L }_orgThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_org(x, y) represents { R_orgThe pixel value L of the pixel point with the coordinate position (x, y) in (x, y) } is_dis(x, y) represents { L }_dis(x, y) } the pixel value of the pixel point with the coordinate position of (x, y), R_dis(x, y) represents { R_disThe coordinate position in (x, y) is the pixel value of the pixel point of (x, y);

secondly, extracting { L by using visual masking effect of human stereoscopic vision perception on background illumination and contrast_dis(x, y) } binocular minimum perceivable change image, notedWherein,represents { L_dis(x, y) } binocular minimum perceivable change imageThe middle coordinate position is the pixel value of the pixel point of (x, y);

(iii) calculating { L_org(x,y)}、{R_org(x,y)}、{L_dis(x,y)}、{R_disEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directions; then obtain { L_org(x,y)}、{R_org(x,y)}、{L_dis(x,y)}、{R_disThe amplitude and the phase of each pixel point in (x, y) in different scales and directions; then according to { L_org(x, y) } and { R }_orgAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_orgEnergy diagram at different scales and directions, and is recorded asAnd according to { L_dis(x, y) } and { R }_disAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_disEnergy diagram at different scales and directions, and is recorded asWherein,to representThe pixel value of the pixel point with the middle coordinate position (x, y) in different scales and directions,to representThe pixel values of the pixel points with the middle coordinate positions (x, y) in different scales and directions, alpha represents the scale factor of the filter adopted by filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter adopted by filtering, and theta is more than or equal to 1 and less than or equal to 4;

fourthly, according to S_orgEnergy diagram at different scales and directionsAnd S_disEnergy diagram at different scales and directionsCalculating S_disThe objective evaluation metric value of each pixel point in S_disThe objective evaluation metric value of the pixel point with the middle coordinate position (x, y) is marked as Q (x, y),

<math> <mrow> <mi>Q</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mi>Σ</mi> <mrow> <mi>θ</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>4</mn> </munderover> <munderover> <mi>Σ</mi> <mrow> <mi>α</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>4</mn> </munderover> <mi>arccos</mi> <mrow> <mo>(</mo> <mfrac> <mrow> <mn>2</mn> <mo>×</mo> <msubsup> <mi>BE</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>org</mi> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>×</mo> <msubsup> <mi>BE</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>dis</mi> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>T</mi> <mn>1</mn> </msub> </mrow> <mrow> <msubsup> <mi>BE</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>org</mi> </msubsup> <msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <msubsup> <mi>BE</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>dis</mi> </msubsup> <msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <msub> <mi>T</mi> <mn>1</mn> </msub> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>/</mo> <mn>16</mn> <mo>,</mo> </mrow> </math>

wherein arccos () is an inverted cosine function, T₁Is a control parameter;

according to S_disAnd the sum of objective evaluation metrics of each pixel point { L_dis(x, y) } binocular minimum perceivable change imageCalculating S using binocular visual masking effect of human visual system_disThe objective evaluation metric value for reflecting the binocular visual masking effect is marked as Q_bm，

<math> <mrow> <msub> <mi>Q</mi> <mi>bm</mi> </msub> <mo>=</mo> <mfrac> <mrow> <munder> <mi>Σ</mi> <mrow> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>&Element;</mo> <mi>Ω</mi> </mrow> </munder> <mi>Q</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>×</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msubsup> <mi>J</mi> <mi>L</mi> <mi>dis</mi> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>)</mo> </mrow> </mrow> <mrow> <munder> <mi>Σ</mi> <mrow> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>&Element;</mo> <mi>Ω</mi> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msubsup> <mi>J</mi> <mi>L</mi> <mi>dis</mi> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> </mrow> </math>

Wherein Ω represents a pixel domain range;

according to S_disAnd the objective evaluation metric value of each pixel point in the image data and S_disEnergy diagram at different scales and directionsCalculating S by using the response characteristics of the human visual system to the binocular energy intensity_disThe objective evaluation metric value for reflecting the binocular energy intensity is marked as Q_be，

<math> <mrow> <msub> <mi>Q</mi> <mi>be</mi> </msub> <mo>=</mo> <mfrac> <mrow> <munder> <mi>Σ</mi> <mrow> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>&Element;</mo> <mi>Ω</mi> </mrow> </munder> <mi>Q</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>×</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msup> <mi>BE</mi> <mi>dis</mi> </msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>)</mo> </mrow> </mrow> <mrow> <munder> <mi>Σ</mi> <mrow> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>&Element;</mo> <mi>Ω</mi> </mrow> </munder> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msup> <mi>BE</mi> <mi>dis</mi> </msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> </mrow> </math>

Wherein,

to S_disObjective evaluation metric Q for reflecting binocular visual masking effect_bmAnd S_disObjective evaluation metric Q for reflecting binocular energy intensity_beCarrying out fusion to obtain S_disThe predicted value of the objective evaluation of image quality is marked as Q_fin，Q_fin=(Q_bm)^γ(Q_be)^βWherein γ and β are weight parameters.

The concrete process of the second step is as follows:

② 1, calculating { L_disVisualization threshold set of luminance masking effect of (x, y) }, denoted as { T }_l(x,y)}，Wherein, T_l(x, y) represents { L }_disVisualization threshold of brightness masking effect of pixel point with coordinate position (x, y) in (x, y) }Value, bg_l(x, y) represents { L }_disThe average value of the brightness of all pixel points in an NxN neighborhood window taking a pixel point with a coordinate position (x, y) as the center in (x, y) }, wherein N is more than or equal to 1;

2, calculating { L_disVisualization threshold set of contrast masking effect of (x, y) }, denoted as { T }_c(x,y)}，T_c(x,y)=K(bg_l(x,y))+eh_l(x, y) wherein T_c(x, y) represents { L }_disThe coordinate position in (x, y) is the visual threshold value of the contrast masking effect of the pixel point of (x, y), eh_l(x, y) represents the pair { L }_disThe pixel points with the coordinate positions (x, y) in (x, y) are respectively subjected to edge filtering in the horizontal direction and the vertical direction to obtain an average gradient value K (bg)_l(x,y))=-10^-6×(0.7×bg_l(x,y)²+32×bg_l(x,y))+0.07；

2- (3) pairs of { L_disVisualization threshold set of luminance masking effects of (x, y) } { T_l(x, y) } and a visual threshold set of contrast masking effects { T }_c(x, y) } to obtain { L_dis(x, y) } binocular minimum perceivable change image, notedWill be provided withThe pixel value of the pixel point with the middle coordinate position (x, y) is recorded as

J_{L}^{dis} (x, y) = T_{l} (x, y) + T_{c} (x, y) .

And N =5 is taken in the step II-1.

The concrete process of the step III is as follows:

③ 1, adopting log-Garbor filter pair { L_org(x, y) is filtered to obtain { L }_orgEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directions are converted into { L }_orgEven symmetric frequency responses of pixel points with coordinate positions (x, y) in different scales and directions in (x, y) are recorded asWill { L_orgThe odd symmetric frequency response of the pixel point with the coordinate position (x, y) in different scales and directions is recorded asWherein alpha represents the scale factor of the filter used for filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter used for filtering, and theta is more than or equal to 1 and less than or equal to 4;

③ 2, calculate { L_orgThe amplitude and phase of each pixel point in (x, y) in different scales and directions will be { L }_orgThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded as Will { L_orgThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded as

<math> <mrow> <msubsup> <mi>LP</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>org</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>arctan</mi> <mrow> <mo>(</mo> <mfrac> <mrow> <msubsup> <mi>e</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>L</mi> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msubsup> <mi>o</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>L</mi> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </math>

Wherein arctan () is an inverse tangent function;

③ 3, obtaining { L ] according to the steps from the third step to the third step_orgThe operation process of the amplitude and the phase of each pixel point in (x, y) } in different scales and directions is carried out to obtain { R } in the same way_org(x,y)}、{L_dis(x,y)}、{R_disThe amplitude and phase of each pixel point in (x, y) in different scales and directions will be { R }_orgThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded asWill { R_orgThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded asWill { L_disThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded asWill { L_disThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded asWill { R_disThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded asWill { R_disThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded as

Thirdly-4, calculating L by adopting a block matching method_org(x, y) } and { R }_org(x, y) } parallax images, noted asWherein,to representThe middle coordinate position is the pixel value of the pixel point of (x, y);

③ 5 according to { L_org(x, y) } and { R }_orgAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_orgParallax image between (x, y) } sCalculating the pixel value of each pixel point in S_orgEnergy diagram at different scales and directions, and is recorded asWill be provided withThe pixel values of the pixel points with the middle coordinate position (x, y) in different scales and directions are recorded as

Wherein cos () is a cosine-taking function,represents { R_org(x, y) } coordinate position ofThe amplitudes of the pixel points of (a) at different scales and directions,represents { R_org(x, y) } coordinate position ofThe phases of the pixel points in different scales and directions;

③ 6 according to { L_dis(x, y) } and { R }_disAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_orgParallax image between (x, y) } sCalculating the pixel value of each pixel point in S_disEnergy diagram at different scales and directions, and is recorded asWill be provided withThe pixel values of the pixel points with the middle coordinate position (x, y) in different scales and directions are recorded as

Wherein,represents { R_dis(x, y) } coordinate position ofThe amplitudes of the pixel points of (a) at different scales and directions,represents { R_dis(x, y) } coordinate position ofThe phase of the pixel point in different scales and directions.

Taking T₁Is 16.

In the step (c), gamma =0.7755 and beta =0.0505 are taken.

Compared with the prior art, the invention has the advantages that:

1) according to the method, the energy graphs of the original undistorted stereo image in different scales and directions and the energy graphs of the distorted stereo image to be evaluated in different scales and directions are respectively calculated, so that the objective evaluation metric value of each pixel point in the distorted stereo image to be evaluated is obtained, and the evaluation result is more perceptually accordant with a human visual system.

2) The method obtains the binocular minimum perceptible change image according to the stereoscopic vision characteristics of human eyes, and fuses the objective evaluation metric values of each pixel point in the distorted stereoscopic image to be evaluated, so that the evaluation result can reflect the binocular vision masking effect, and the correlation between the objective evaluation result and subjective perception is effectively improved.

3) According to the method, objective evaluation metric values of all pixel points in the distorted three-dimensional image to be evaluated are fused according to the energy graphs in different scales and directions, so that the evaluation result can reflect the response characteristic of a human visual system to binocular energy intensity, and the correlation between the objective evaluation result and subjective perception is effectively improved.

Drawings

FIG. 1 is a block diagram of an overall implementation of the method of the present invention;

fig. 2a is a left viewpoint image of Akko (640 × 480 size) stereo image;

fig. 2b is a right viewpoint image of an Akko (size 640 × 480) stereoscopic image;

fig. 3a is a left viewpoint image of an altmobit (size 1024 × 768) stereoscopic image;

fig. 3b is a right view image of an altmobit (size 1024 × 768) stereoscopic image;

fig. 4a is a left viewpoint image of a balloon (size 1024 × 768) stereoscopic image;

fig. 4b is a right viewpoint image of a balloon (size 1024 × 768) stereoscopic image;

fig. 5a is a left viewpoint image of a Doorflower (size 1024 × 768) stereoscopic image;

fig. 5b is a right viewpoint image of a Doorflower (size 1024 × 768) stereoscopic image;

fig. 6a is a left view image of a Kendo (size 1024 × 768) stereoscopic image;

fig. 6b is a right view image of a Kendo (size 1024 × 768) stereoscopic image;

fig. 7a is a left view image of a LeaveLaptop (size 1024 × 768) stereoscopic image;

fig. 7b is a right view image of a LeaveLaptop (size 1024 × 768) stereoscopic image;

fig. 8a is a left viewpoint image of a lovedual 1 (size 1024 × 768) stereoscopic image;

fig. 8b is a right viewpoint image of a lovedual 1 (size 1024 × 768) stereoscopic image;

fig. 9a is a left view image of a newsapper (size 1024 × 768) stereoscopic image;

fig. 9b is a right view image of a newsapper (size 1024 × 768) stereoscopic image;

FIG. 10a is a left viewpoint image of Puppy (size 720 × 480) stereo image;

FIG. 10b is a right viewpoint image of Puppy (size 720 × 480) stereoscopic image;

fig. 11a is a left viewpoint image of a Soccer2 (size 720 × 480) stereoscopic image;

fig. 11b is a right viewpoint image of a Soccer2 (size 720 × 480) stereoscopic image;

fig. 12a is a left viewpoint image of a Horse (size 720 × 480) stereoscopic image;

fig. 12b is a right view image of a Horse (size 720 × 480) stereoscopic image;

fig. 13a is a left viewpoint image of an Xmas (size 640 × 480) stereoscopic image;

fig. 13b is a right view image of an Xmas (size 640 × 480) stereoscopic image;

fig. 14 is a scatter diagram of the difference between the objective evaluation prediction value of image quality and the average subjective score for each distorted stereoscopic image.

Detailed Description

The invention is described in further detail below with reference to the accompanying examples.

The invention provides a stereo image quality objective evaluation method based on an energy diagram, the overall implementation block diagram of which is shown in figure 1, and the processing process of the method is as follows: firstly, acquiring an energy diagram of the original undistorted stereo image in different scales and directions according to even symmetric frequency response and odd symmetric frequency response of each pixel point in the left viewpoint image and the right viewpoint image of the original undistorted stereo image in different scales and directions and a pixel value of each pixel point in a parallax image between the left viewpoint image and the right viewpoint image of the original undistorted stereo image, acquiring energy graphs of the distorted stereo image to be evaluated in different scales and directions according to even symmetric frequency response and odd symmetric frequency response of each pixel point in the left viewpoint image and the right viewpoint image of the distorted stereo image to be evaluated in different scales and directions and pixel values of each pixel point in a parallax image between the left viewpoint image and the right viewpoint image of the original undistorted stereo image; then obtaining an objective evaluation metric value of each pixel point in the distorted stereo image to be evaluated according to the two energy maps; obtaining an objective evaluation metric value of the distorted three-dimensional image to be evaluated for reflecting a binocular visual masking effect according to the objective evaluation metric value of each pixel point in the distorted three-dimensional image to be evaluated and the binocular minimum perceptible change image of the left viewpoint image of the distorted three-dimensional image to be evaluated, and obtaining an objective evaluation metric value of the distorted three-dimensional image to be evaluated for reflecting binocular energy intensity according to the objective evaluation metric value of each pixel point in the distorted three-dimensional image to be evaluated and energy maps of the distorted three-dimensional image to be evaluated in different scales and directions; and finally, fusing an objective evaluation metric value for reflecting binocular visual masking effect and an objective evaluation metric value for reflecting binocular energy intensity of the distorted three-dimensional image to be evaluated to obtain an objective evaluation prediction value of the image quality of the distorted three-dimensional image to be evaluated. The method specifically comprises the following steps:

making S_orgFor original undistorted stereo image, let S_disFor the distorted stereo image to be evaluated, S_orgIs noted as { L_org(x, y) }, adding S_orgRight viewpoint ofThe image is noted as { R_org(x, y) }, adding S_disIs noted as { L_dis(x, y) }, adding S_disIs noted as { R_dis(x, y) }, wherein (x, y) denotes a coordinate position of a pixel point in the left viewpoint image and the right viewpoint image, x is 1. ltoreq. x.ltoreq.W, y is 1. ltoreq. y.ltoreq.H, W denotes a width of the left viewpoint image and the right viewpoint image, H denotes a height of the left viewpoint image and the right viewpoint image, L is L_org(x, y) represents { L }_orgThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_org(x, y) represents { R_orgThe pixel value L of the pixel point with the coordinate position (x, y) in (x, y) } is_dis(x, y) represents { L }_disThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_dis(x, y) represents { R_disAnd the coordinate position in the (x, y) is the pixel value of the pixel point of (x, y).

The human visual characteristics indicate that the human eye is imperceptible to a property or noise that changes less in the image unless the intensity of the change of the property or noise exceeds a threshold, which is the minimum perceptible distortion (JND). However, the visual masking effect of human eyes is a local effect, which is influenced by background illumination, texture complexity and other factors, and the brighter the background is, the more complex the texture is, and the higher the threshold value is. Therefore, the invention extracts L by using the visual masking effect of human stereoscopic vision perception on background illumination and contrast_dis(x, y) } binocular minimum perceivable change image, notedWherein,represents { L_dis(x, y) } binocular minimum perceivable change imageThe middle coordinate position is the pixel value of the pixel point of (x, y).

In this embodiment, the specific process of step two is:

② 1, calculating { L_disVisualization threshold set of luminance masking effect of (x, y) }, denoted as { T }_l(x,y)}，Wherein, T_l(x, y) represents { L }_disThe coordinate position in (x, y) is the visual threshold value of the brightness masking effect of the pixel point of (x, y), bg_l(x, y) represents { L }_disIn (x, y) }, the pixel with the coordinate position (x, y) as the center is the average value of the brightness of all the pixels in the N × N neighborhood window, where N is greater than or equal to 1, and in this embodiment, N =5 is taken.

2, calculating { L_disVisualization threshold set of contrast masking effect of (x, y) }, denoted as { T }_c(x,y)}，T_c(x,y)=K(bg_l(x,y))+eh_l(x, y) wherein T_c(x, y) represents { L }_disThe coordinate position in (x, y) is the visual threshold value of the contrast masking effect of the pixel point of (x, y), eh_l(x, y) represents the pair { L }_disThe pixel points with the coordinate positions (x, y) in (x, y) are respectively subjected to edge filtering in the horizontal direction and the vertical direction to obtain an average gradient value K (bg)_l(x,y))=-10^-6×(0.7×bg_l(x,y)²+32×bg_l(x,y))+0.07。

J_{L}^{dis} (x, y) = T_{l} (x, y) + T_{c} (x, y) .

(iii) calculating { L_org(x,y)}、{R_org(x,y)}、{L_dis(x,y)}、{R_disEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directions; then obtain { L_org(x,y)}、{R_org(x,y)}、{L_dis(x,y)}、{R_disThe amplitude and the phase of each pixel point in (x, y) in different scales and directions; then according to { L_org(x, y) } and { R }_orgAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_orgEnergy diagram at different scales and directions, and is recorded asAnd according to { L_dis(x, y) } and { R }_disAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_disEnergy diagram at different scales and directions, and is recorded asWherein,to representThe pixel value of the pixel point with the middle coordinate position (x, y) in different scales and directions,to representAnd the pixel values of the pixel points with the middle coordinate positions (x, y) in different scales and directions, wherein alpha represents the scale factor of the filter adopted by filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter adopted by filtering, and theta is more than or equal to 1 and less than or equal to 4.

In this embodiment, the specific process of step (c) is:

③ 1, adopting log-Garbor filter pair { L_org(x, y) is filtered to obtain { L }_orgEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directions are converted into { L }_orgEven symmetric frequency responses of pixel points with coordinate positions (x, y) in different scales and directions in (x, y) are recorded asWill { L_orgThe odd symmetric frequency response of the pixel point with the coordinate position (x, y) in different scales and directions is recorded asWherein alpha represents the scale factor of the filter used for filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter used for filtering, and theta is more than or equal to 1 and less than or equal to 4.

Wherein arctan () is an arctangent function.

③ 3, obtaining { L ] according to the steps from the third step to the third step_orgThe operation process of the amplitude and the phase of each pixel point in (x, y) } in different scales and directions is carried out to obtain { R } in the same way_org(x,y)}、{L_dis(x,y)}、{R_disThe amplitude and phase of each pixel point in (x, y) in different scales and directions will be { R }_orgThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded asWill { R_orgThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded asWill { L_disThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded asWill { L_disThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded asWill { R_disThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded asWill { R_disThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded asFor example: obtaining { L_disThe amplitudes of pixel points with (x, y) as coordinate positions in (x, y) in different scales and directionsAnd phaseThe process comprises the following steps: a. using log-Garbor filter pairs { L_dis(x, y) is filtered to obtain { L }_disEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directionsSymmetric frequency response, will { L_disEven symmetric frequency responses of pixel points with coordinate positions (x, y) in different scales and directions in (x, y) are recorded asWill { L_disThe odd symmetric frequency response of the pixel point with the coordinate position (x, y) in different scales and directions is recorded asWherein alpha represents the scale factor of the filter used for filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter used for filtering, and theta is more than or equal to 1 and less than or equal to 4; calculation of { L_disThe amplitude and phase of each pixel point in (x, y) in different scales and directions will be { L }_disThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded as

Will { L_disThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded as

<math> <mrow> <msubsup> <mi>LP</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mrow> <mi>L</mi> <mo>,</mo> <mi>dis</mi> </mrow> </msubsup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>arctan</mi> <mrow> <mo>(</mo> <mfrac> <mrow> <msup> <msubsup> <mi>e</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>L</mi> </msubsup> <mo>′</mo> </msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msup> <msubsup> <mi>o</mi> <mrow> <mi>α</mi> <mo>,</mo> <mi>θ</mi> </mrow> <mi>L</mi> </msubsup> <mo>′</mo> </msup> <mrow> <mo>(</mo> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>.</mo> </mrow> </math>

Thirdly-4, calculating L by adopting a block matching method_org(x, y) } and { R }_org(x, y) } parallax images, noted asWherein,to representThe middle coordinate position is the pixel value of the pixel point of (x, y).

Wherein cos () is a cosine-taking function,represents { R_org(x, y) } coordinate position ofThe amplitudes of the pixel points of (a) at different scales and directions,represents { R_org(x, y) } coordinate position ofThe phase of the pixel point in different scales and directions.

Fourthly, according to S_orgEnergy diagram at different scales and directionsAnd S_disEnergy diagram at different scales and directionsCalculating S_disThe objective evaluation metric value of each pixel point in S_disThe objective evaluation metric values of all the pixel points in (1) are expressed as { Q (x, y) } by a set, and S is expressed as_disThe objective evaluation metric value of the pixel point with the middle coordinate position (x, y) is marked as Q (x, y),

wherein arccos () is an inverted cosine function, T₁To control the parameters, in this embodiment, T is taken₁Is 16.

The human visual system characteristic shows that human eyes are sensitive to distortion of the area with small binocular perceptibility change value. The invention is thus based on S_disAnd the sum of objective evaluation metrics of each pixel point { L_dis(x, y) } binocular minimum perceivable change imageCalculating S using binocular visual masking effect of human visual system_disThe objective evaluation metric value for reflecting the binocular visual masking effect is marked as Q_bm，Where Ω represents the pixel domain range.

The characteristics of the human visual system show that human eyes can generate stronger response to areas with larger binocular energy intensity. The invention is thus based on S_disAnd the objective evaluation metric value of each pixel point in the image data and S_disEnergy diagram at different scales and directionsCalculating S by using the response characteristics of the human visual system to the binocular energy intensity_disThe objective evaluation metric value for reflecting the binocular energy intensity is marked as Q_be，

Wherein,

to S_disObjective evaluation metric Q for reflecting binocular visual masking effect_bmAnd S_disObjective evaluation metric Q for reflecting binocular energy intensity_beCarrying out fusion to obtain S_disThe predicted value of the objective evaluation of image quality is marked as Q_fin，Q_fin=(Q_bm)^γ(Q_be)^βWhere γ and β are weight parameters, in this embodiment, γ =0.7755 and β =0.0505 are taken.

In the present embodiment, 12 undistorted stereoscopic images shown in fig. 2a and 2b, fig. 3a and 3b, fig. 4a and 4b, fig. 5a and 5b, fig. 6a and 6b, fig. 7a and 7b, fig. 8a and 8b, fig. 9a and 9b, fig. 10a and 10b, fig. 11a and 11b, fig. 12a and 12b, and fig. 13a and 13b are used to create the stereoscopic image without distortionThe distorted stereo image S obtained by the method of the invention is analyzed by using 312 distorted stereo images under the conditions of different degrees of JPEG compression, JPEG2000 compression, Gaussian blur, white noise and H.264 coding distortion_disThe correlation between the predicted value and the average subjective score difference is objectively evaluated, wherein 60 distorted stereoscopic images are compressed by JPEG, 60 distorted stereoscopic images are compressed by JPEG2000, 60 distorted stereoscopic images are compressed by Gaussian Blur, 60 distorted stereoscopic images are blurred by White Noise (White Noise), and 72 distorted stereoscopic images are encoded by H.264. And respectively obtaining average subjective score difference values of 312 distorted stereo images by using the existing subjective quality evaluation method, and recording the average subjective score difference values as DMOS, DMOS =100-MOS, wherein MOS represents the subjective score average value, DMOS belongs to [0,100 ]]。

In this embodiment, 4 common objective parameters of the image quality evaluation method are used as evaluation indexes, that is, Pearson correlation coefficient (PLCC), Spearman correlation coefficient (SROCC), Kendall correlation coefficient (KROCC), mean square error (RMSE), accuracy of the stereo image evaluation objective model in which distortion is reflected by PLCC and rmocc, and monotonicity of SROCC and KROCC is reflected by KROCC under a nonlinear regression condition. The image quality objective evaluation predicted value of the distorted stereo image calculated according to the method is subjected to five-parameter Logistic function nonlinear fitting, and the higher the PLCC, SROCC and KROCC values are, the lower the RMSE value is, the better the correlation between the objective evaluation method and the average subjective score difference is. The PLCC, SROCC, KROCC and RMSE coefficients reflecting the performance of the three-dimensional image objective evaluation model are shown in the table 1, and the data listed in the table 1 shows that the correlation between the final image quality objective evaluation predicted value of the distorted three-dimensional image obtained by the method and the average subjective score difference value is very high, so that the objective evaluation result is fully consistent with the result of human eye subjective perception, and the effectiveness of the method is sufficiently proved.

Fig. 14 shows a scatter diagram of the difference between the objective evaluation prediction value of the image quality and the average subjective score of 312 distorted stereoscopic images, and the more concentrated the scatter is, the better the consistency between the objective evaluation result and the subjective perception is. As can be seen from fig. 14, the scatter diagram obtained by the method of the present invention is more concentrated, and the goodness of fit with the subjective evaluation data is higher.

TABLE 1 correlation between objective evaluation prediction value and subjective score of image quality of distorted stereoscopic image obtained by the method of the present invention

Claims

1. A three-dimensional image quality objective evaluation method based on an energy map is characterized in that the processing process is as follows: firstly, acquiring an energy diagram of the original undistorted stereo image in different scales and directions according to even symmetric frequency response and odd symmetric frequency response of each pixel point in the left viewpoint image and the right viewpoint image of the original undistorted stereo image in different scales and directions and a pixel value of each pixel point in a parallax image between the left viewpoint image and the right viewpoint image of the original undistorted stereo image, acquiring energy graphs of the distorted stereo image to be evaluated in different scales and directions according to even symmetric frequency response and odd symmetric frequency response of each pixel point in the left viewpoint image and the right viewpoint image of the distorted stereo image to be evaluated in different scales and directions and pixel values of each pixel point in a parallax image between the left viewpoint image and the right viewpoint image of the original undistorted stereo image; then obtaining an objective evaluation metric value of each pixel point in the distorted stereo image to be evaluated according to the two energy maps; obtaining an objective evaluation metric value of the distorted three-dimensional image to be evaluated for reflecting a binocular visual masking effect according to the objective evaluation metric value of each pixel point in the distorted three-dimensional image to be evaluated and the binocular minimum perceptible change image of the left viewpoint image of the distorted three-dimensional image to be evaluated, and obtaining an objective evaluation metric value of the distorted three-dimensional image to be evaluated for reflecting binocular energy intensity according to the objective evaluation metric value of each pixel point in the distorted three-dimensional image to be evaluated and energy maps of the distorted three-dimensional image to be evaluated in different scales and directions; finally, objective evaluation metric values used for reflecting binocular visual masking effects and objective evaluation metric values used for reflecting binocular energy intensity of the distorted three-dimensional image to be evaluated are fused to obtain an objective evaluation prediction value of the image quality of the distorted three-dimensional image to be evaluated;

here, let S_orgFor original undistorted stereo image, let S_disFor the distorted stereo image to be evaluated, S_orgIs noted as { L_org(x, y) }, adding S_orgIs noted as { R_org(x, y) }, adding S_disIs noted as { L_dis(x, y) }, adding S_disIs noted as { R_dis(x, y) }, wherein (x, y) denotes a coordinate position of a pixel point in the left viewpoint image and the right viewpoint image, x is 1. ltoreq. x.ltoreq.W, y is 1. ltoreq. y.ltoreq.H, W denotes a width of the left viewpoint image and the right viewpoint image, H denotes a height of the left viewpoint image and the right viewpoint image, L is L_org(x, y) represents { L }_orgThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_org(x, y) represents { R_org(x, y) having (x, y) as the coordinate positionPixel value, L, of a pixel point_dis(x, y) represents { L }_disThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_dis(x, y) represents { R_disThe coordinate position in (x, y) is the pixel value of the pixel point of (x, y); then according to { L_org(x, y) } and { R }_orgAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_orgEnergy diagram at different scales and directions, and is recorded asAnd according to { L_dis(x, y) } and { R }_disAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_disEnergy diagram at different scales and directions, and is recorded asWherein,to representThe pixel value of the pixel point with the middle coordinate position (x, y) in different scales and directions,to representAnd the pixel values of the pixel points with the middle coordinate positions (x, y) in different scales and directions, wherein alpha represents the scale factor of the filter adopted by filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter adopted by filtering, and theta is more than or equal to 1 and less than or equal to 4.

2. The method for objectively evaluating the quality of a stereoscopic image based on an energy map according to claim 1, characterized in that it comprises the following steps:

making S_orgFor original undistorted stereo image, let S_disFor the distorted stereo image to be evaluated, S_orgIs noted as { L_org(x, y) }, adding S_orgIs noted as { R_org(x, y) }, adding S_disIs noted as { L_dis(x, y) }, adding S_disIs noted as { R_dis(x, y) }, wherein (x, y) denotes a coordinate position of a pixel point in the left viewpoint image and the right viewpoint image, x is 1. ltoreq. x.ltoreq.W, y is 1. ltoreq. y.ltoreq.H, W denotes a width of the left viewpoint image and the right viewpoint image, H denotes a height of the left viewpoint image and the right viewpoint image, L is L_org(x, y) represents { L }_orgThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_org(x, y) represents { R_orgThe pixel value L of the pixel point with the coordinate position (x, y) in (x, y) } is_dis(x, y) represents { L }_disThe coordinate position in (x, y) } is the pixel value of the pixel point with (x, y), R_dis(x, y) represents { R_disThe coordinate position in (x, y) is the pixel value of the pixel point of (x, y);

(iii) calculating { L_org(x,y)}、{R_org(x,y)}、{L_dis(x,y)}、{R_disEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directions; then obtain { L_org(x,y)}、{R_org(x,y)}、{L_dis(x,y)}、{R_disThe amplitude and the phase of each pixel point in (x, y) in different scales and directions; then according to { L_org(x, y) } and { R }_orgAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_orgEnergy diagram at different scales and directions, and is recorded asAnd according to { L_dis(x, y) } and { R }_disAmplitude and phase of each pixel point in (x, y) in different scales and directions, and { L }_org(x, y) } and { R }_org(x, y) } calculating S from the pixel value of each pixel in the parallax image_disEnergy diagram at different scales and directions, and is recorded asWherein,to representThe pixel value of the pixel point with the middle coordinate position (x, y) in different scales and directions,to representThe pixel values of the pixel points with the (x, y) coordinate positions in different scales and directions are determined, alpha represents the scale factor of the filter adopted by filtering, alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter adopted by filtering, and theta is more than or equal to 1 and less than or equal to 4θ≤4；

wherein arccos () is an inverted cosine function, T₁Is a control parameter;

according to S_disAnd the sum of objective evaluation metrics of each pixel point { L_dis(x, y) } binocular minimum perceivable change imageCalculating S using binocular visual masking effect of human visual system_disThe objective evaluation metric value for reflecting the binocular visual masking effect is marked as Q_bm，Wherein Ω represents a pixel domain range;

according to S_disAnd the objective evaluation metric value of each pixel point in the image data and S_disEnergy diagram at different scales and directionsCalculating S by using the response characteristics of the human visual system to the binocular energy intensity_disThe objective evaluation metric value for reflecting the binocular energy intensity is marked as Q_be，Wherein,

to S_disObjective evaluation metric Q for reflecting binocular visual masking effect_bmAnd S_disObjective evaluation metric Q for reflecting binocular energy intensity_beCarrying out fusion to obtain S_disThe predicted value of the objective evaluation of image quality is marked as Q_fin，Q_fin＝(Q_bm)^γ(Q_be)^βWherein γ and β are weight parameters.

3. The objective evaluation method for the quality of the stereo image based on the energy map as claimed in claim 2, characterized in that the concrete process of the step (II) is as follows:

② 1, calculating { L_disVisualization threshold set of luminance masking effect of (x, y) }, denoted as { T }_l(x,y)}，Wherein, T_l(x, y) represents { L }_disThe coordinate position in (x, y) is the visual threshold value of the brightness masking effect of the pixel point of (x, y), bg_l(x, y) represents { L }_disThe average value of the brightness of all pixel points in an NxN neighborhood window taking a pixel point with a coordinate position (x, y) as the center in (x, y) }, wherein N is more than or equal to 1;

2, calculating { L_disVisualization threshold set of contrast masking effect of (x, y) }, denoted as { T }_c(x,y)}，T_c(x,y)＝K(bg_l(x,y))+eh_l(x, y) wherein T_c(x, y) represents { L }_disThe coordinate position in (x, y) is the visual threshold value of the contrast masking effect of the pixel point of (x, y), eh_l(x, y) represents the pair { L }_disThe pixel points with the coordinate positions (x, y) in (x, y) are respectively subjected to edge filtering in the horizontal direction and the vertical direction to obtain an average gradient value K (bg)_l(x,y))＝-10^-6×(0.7×bg_l(x,y)²+32×bg_l(x,y))+0.07；

J_{L}^{dis} (x, y) = T_{l} (x, y) + T_{c} (x, y) .

4. The method according to claim 3, wherein in step (2), N is 5.

5. The objective evaluation method for stereo image quality based on energy map according to any one of claims 2 to 4, characterized in that the concrete process of the third step is:

③ 1, adopting log-Garbor filter pair { L_org(x, y) is filtered to obtain { L }_orgEven symmetric frequency response and odd symmetric frequency response of each pixel point in (x, y) } in different scales and directions are converted into { L }_orgEven symmetric frequency responses of pixel points with coordinate positions (x, y) in different scales and directions in (x, y) are recorded asWill { L_orgThe odd symmetric frequency response of the pixel point with the coordinate position (x, y) in different scales and directions is recorded asWhere α represents the scale of the filter employed for filteringThe factor alpha is more than or equal to 1 and less than or equal to 4, theta represents the direction factor of the filter used for filtering, and theta is more than or equal to 1 and less than or equal to 4;

③ 2, calculate { L_orgThe amplitude and phase of each pixel point in (x, y) in different scales and directions will be { L }_orgThe amplitudes of the pixel points with the coordinate positions (x, y) in the (x, y) at different scales and directions are recorded as Will { L_orgThe phase positions of the pixel points with the coordinate positions (x, y) in (x, y) at different scales and directions are recorded as Wherein arctan () is an inverse tangent function;

6. The objective evaluation method for stereo image quality based on energy map as claimed in claim 5, wherein T is taken in the step (iv)₁Is 16.

7. The method as claimed in claim 6, wherein in step (c) γ 0.7755 and β 0.0505 are included.