CN113473150B - Image processing method and device and computer readable storage device - Google Patents
Image processing method and device and computer readable storage device Download PDFInfo
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Abstract
The application discloses an image processing method, an image processing apparatus and a computer readable storage apparatus. The image processing method comprises the following steps: acquiring first image data; extracting alpha channel data in the first image data; wherein, the alpha channel data is used for describing the transparency of the image; preprocessing the first image data according to the alpha channel data to obtain second image data; and performing compression processing on the second image data. By the mode, the image compression rate can be reduced while the image quality is ensured when the image data is compressed.
Description
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an alpha channel data processing method, an image processing apparatus, and a computer-readable storage apparatus.
Background
With the continuous development of science and technology, various image formats are derived to adapt to different complex situations and requirements. In order to further satisfy the high demand for image quality, among others, image formats with transparency are widely used in various fields such as game design, web page production, and live video broadcasting. An image is typically composed of three color channels, R (Red), G (Green ), and B (Blue ). In addition, the alpha channel is typically used to describe the transparency information of the image. The alpha channel is an 8-bit grayscale channel that represents transparency information in the recorded image with 0-255 grayscale, defining transparent, opaque, and translucent regions, where 0 represents completely transparent, 255 represents completely opaque, and the intermediate values represent translucency. Because the image adds an alpha channel in the original color information, the image data information is further increased, and in order to meet the quality requirement of transmission and save resources, the image data is usually selected to be compressed and transmitted.
In the prior art, a method for compressing an image file containing an alpha channel generally comprises the following steps:
1. and carrying out lossless compression on the picture to obtain a compressed file. The method can restore the original data including the alpha channel data after decompression without causing any distortion. However, the compression rate of lossless compression is usually only about 60%, and the size of the compressed file is still large, which sometimes cannot meet the requirements of storing and transmitting the picture file.
2. And carrying out lossy compression on the pictures to obtain a compressed file. Although lossy compression greatly reduces the compression rate of pictures, which can usually reach about 14%, the conventional lossy compression method usually sacrifices alpha channel data, and the decompressed file obtained after decompression is seriously distorted relative to the original file, so that the specific effect of the original picture cannot be realized.
Disclosure of Invention
The present application mainly aims to provide an image processing method, an image processing apparatus, and a computer-readable storage device, which can effectively improve the technical problem of further reducing the image compression ratio while ensuring the image quality when image data is compressed.
In order to solve the technical problem, the present application adopts a technical solution that: an image processing method is provided. The method comprises the following steps: acquiring first image data; extracting alpha channel data in the first image data; wherein, alpha channel data is used for describing the transparency of the image; preprocessing the first image data according to the alpha channel data to obtain second image data; and performing compression processing on the second image data.
In order to solve the above technical problem, the second technical solution adopted by the present application is: there is provided an image processing apparatus comprising a memory for storing program data executable by a processor to implement the image processing method described above and a processor.
In order to solve the above technical problem, a third technical solution adopted by the present application is: there is provided a computer readable storage device storing program data executable by a processor to implement the image processing method described above.
The beneficial effect of this application is: the data characteristics of the contained alpha channel data are fully analyzed before the image with the alpha channel data is compressed, and the corresponding processing such as deletion or integration is carried out on the alpha channel data of the image, so that the data volume for describing the alpha channel data is reduced. On the basis of ensuring the image quality, the bit number of the code is reduced, and the compression efficiency is improved.
Drawings
FIG. 1 is a schematic flow chart diagram of a first embodiment of an image processing method of the present application;
FIG. 2 is a schematic flowchart of an embodiment of S13 in the first embodiment of the image processing method of the present application;
FIG. 3 is a flowchart illustrating a first embodiment of S22 in an embodiment of the image processing method S13 of the present application;
FIG. 4 is a diagram illustrating the results of a specific process flow of the first embodiment of the present application S22;
FIG. 5 is a flowchart illustrating a second embodiment of S22 in one embodiment of the image processing method S13 of the present application;
FIG. 6 is a flowchart illustrating a third embodiment of S22 in an embodiment of the image processing method S13 of the present application;
FIG. 7 is a flowchart illustrating an embodiment of S23 in an embodiment of the image processing method S13 of the present application;
FIG. 8 is a flowchart illustrating an embodiment of an image processing method S25 of the present application;
FIG. 9 is a schematic diagram of an embodiment of an image processing apparatus according to the present application;
FIG. 10 is a block diagram of an embodiment of a computer readable storage device according to the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Generally, when image data containing alpha channel information is transmitted, lossy compression is selected for color data of an image, that is, RGB data, and lossless compression is selected for alpha channel data, due to respective characteristics of lossy compression and lossless compression. The data characteristics of the alpha channel data are not fully utilized in the mode, and the alpha channel data are still large after being partially compressed.
In order to improve the above technical problem, the present application proposes the following embodiments:
referring to fig. 1, fig. 1 is a schematic flowchart of a first embodiment of an image processing method of the present application, and the specific steps include:
s11: first image data is acquired.
The processing object selected in some embodiments exemplified hereinafter in the present application is a PNG format image containing alpha channel data.
S12, extracting alpha channel data in the first image data.
And judging whether the acquired first data image contains data information related to alpha channel data. If the alpha channel information is included, relevant information is extracted. If not, the processing method related to the alpha channel data described in the present application is not required. The alpha channel data is directly or indirectly contained in the image data, for example, when the image format is an index color format, the tRNS field in the image data contains an alpha value corresponding to the palette, that is, alpha channel information indicating the image data.
And S13, preprocessing the first image data according to the alpha channel data to obtain second image data.
According to the extracted alpha channel data, the data characteristics of the alpha channel data are analyzed, so that a corresponding processing method which does not damage the image quality is carried out, the data volume for describing the alpha channel data is reduced, and the aim of reducing the data compression ratio is fulfilled.
Referring to fig. 2, fig. 2 is a schematic flow chart of an embodiment of S13 in the first embodiment of the image processing method of the present application.
S21: a color format of the first image data is determined.
Whether the acquired image data belongs to an index color format or a true color format, or whether the acquired first image data is to be encoded into the index color format or the true color format is determined, and different image data processing modes are selected according to the color format of the image data.
When it is judged that the color format of the acquired first image data is the index color format, step S22 is executed.
And S22, updating the first palette of the first image data according to the alpha channel data to obtain a second palette.
After analyzing the data characteristics of the alpha channel data, the data is subjected to reduction or integration or the like without affecting the image quality to reduce the data amount of the alpha channel, so that the compression rate is lowered.
Several specific embodiments of the process for updating the palette using alpha channel data are described in detail below.
Referring to fig. 3, fig. 3 is a schematic flowchart of a first embodiment of S22 in an embodiment of the image processing method S13 of the present application.
S31: unifying the color data corresponding to the pixel with the alpha value of 0 in the first palette.
Referring to fig. 4, fig. 4 is an exemplary illustration of the palette processing result with the acquired image data in PNG format. As shown in fig. 4 (a), first, the tRNS field in the image data is read to acquire the first palette. Then, as shown in fig. 4 (b), the RGB components having an alpha value of 0 in the first palette may be unified according to any color component having an index having an alpha value of 0, and in fig. 4 (b), the RGB components may be unified according to the index having a first alpha value of 0.
S32: and reserving one of the indexes with the alpha values of 0 in the first palette, and removing the rest indexes with the alpha values of 0 to obtain a second palette.
And one of the indexes with the alpha value of 0 is reserved, the remaining indexes with the alpha value of 0 and the corresponding palette data are deleted, and the other palette data with the alpha value of not 0 are sequentially filled to obtain a new palette. As shown in fig. 4 (c), the case where the index data having the first alpha value of 0 is retained and the other index data having the alpha value of 0 is deleted to obtain the second palette is exemplified.
Referring to fig. 5, fig. 5 is a schematic flowchart of a second embodiment of S22 in an embodiment of the image processing method S13 of the present application.
S41: palette indices are set for pixels in the first palette in order of smaller alpha values to larger alpha values.
All the alpha values are arranged in the order from small to large, and then the indexes of the palette are set in sequence. It is understood that the order of arrangement is not fixed, but may be from large to small. If the order is from big to small, the palette needs to be filled with empty bits after the subsequent deleting process. Alternatively, this step may be discarded and step S42 may be performed directly.
S42: and deleting the alpha value which is larger than the first set threshold value in the first palette to obtain a second palette.
The transparency threshold N is set as the case may be, with N belonging to 0,255, without substantially affecting the overall quality of the image. Alpha values in the first palette that are greater than the threshold are deleted, such that no encoding is required above the transparency threshold upon compression. Because, for example, when the image data is in the PNG format and the color format is an index color containing tRNS field, the number of alpha values contained in the tRNS field may be smaller than the number of indexes of the palette. When the number of indexes is smaller than the number of indexes of the palette, it is assumed that all remaining palettes have alpha values of 255.
Referring to fig. 6, fig. 6 is a schematic flowchart of a third embodiment of S22 in an embodiment of the image processing method S13 of the present application.
S51: the alpha value is divided into a number of bins and a target bin of the number of bins is determined.
The 0-255 level alpha values are divided into a plurality of intervals, the number of the intervals can be self-limited according to the situation, and the sizes of the intervals can be equal or unequal. And analyzing the extracted alpha channel data, and determining an interval with more alpha values as a target interval.
It can be understood that the distribution of alpha channel data in the image data may also be observed first, and then the division and the next processing are performed for the interval with dense alpha value distribution.
S52: unifying color values of pixels with color value differences smaller than a second set threshold value in pixels with alpha values corresponding to the target interval in the first palette; and unifying the alpha values of the pixels with the color value difference smaller than the second set threshold value to obtain a second color palette.
And comparing pixel values corresponding to the alpha values in the target interval, and representing the pixels with similar colors by using the same color. For example, the alpha values corresponding to the color data of the four pixels (240, 128, 128), (242, 128, 128), (240, 128, 130), (242, 128, 130) are all located between [128,130], then the color component of (241, 128, 129) can be selected to replace the above-mentioned several colors, and the alpha values thereof are unified to 129. In this illustrative example, the second set threshold is 2, that is, the judgment basis of the color proximity is that the color component data difference is within 2. Uniform color data and an intermediate value selected for the alpha value. The specific judgment basis of the similar colors and the calculation process of the finally selected uniform color and alpha value can be defined by self according to the actual situation under the condition of basically not influencing the overall effect of the image. And replacing the corresponding pixel data in the first palette by the unified pixel data to obtain a second palette.
S23: and replacing the first palette in the first image data by the second palette to obtain second image data.
Compared with the first palette, the second palette is deleted or integrated on the basis of the first palette, so that the data volume used for describing alpha channel data through the second palette is less, and the compression rate of image data compression can be reduced.
When it is judged that the color format of the acquired first image data is the true color format, step S24 is executed.
S24: and generating an alpha value index table according to the alpha channel data.
Referring to fig. 7, fig. 7 is a flowchart illustrating a first embodiment of S24 in an embodiment of the image processing method S13 of the present application.
S61: and judging whether the alpha values in the alpha channel data are completely equal.
When the alpha values are completely equal, step S62 is performed.
S62: and deleting the alpha channel data, and constructing an alpha value index table by using the alpha value.
Since the alpha values of all pixels of the image data are equal, the alpha channel data in the image data are deleted and the alpha values are used as an alpha value index table to describe the alpha channel data of the image data.
When the alpha values are not completely equal, step S63 is performed.
S63: it is determined whether the number of unequal alpha values is greater than 128.
When the number of unequal alpha values is greater than 128, step S64 is performed.
S64: the alpha channel data is not processed.
When the unequal alpha values are greater than 128, when the index format is used to describe the alpha channel data, the used index needs to be 8 bits, which is consistent with the 8 bits of the original alpha channel. In this case, the amount of image data is not reduced by using the index format compared with the original format. Therefore, the alpha channel data is not processed, and the subsequent coding is carried out according to the original format.
When the number of unequal alpha values is less than or equal to 128, step S65 is performed.
S65: the index is described with k bits to construct an alpha value index table.
Judging the number of unequal alpha values to 2 k K is one of 1, 2, 3, 4, 5, 6 and 7, and the number of the selected unequal alpha values is less than or equal to 2 k And taking the minimum value of the time k as the bit number of the index of the alpha value channel described by the alpha value index table.
After the alpha value index table is obtained through step S24, step S25 is performed.
S25: and describing alpha channel data according to the alpha value index table to obtain second image data.
And when an alpha value index table describing indexes by using k bits is obtained, adding the alpha value index table into the first image data and obtaining second image data after describing alpha channel data.
When the index table containing only one alpha value data is obtained, as shown in fig. 8, fig. 8 is a specific embodiment of step S25 on the condition that step S62 is executed.
S71: it is determined whether the alpha value is equal to 255.
When the alpha value is equal to 255, step S72 is performed.
S72: the alpha value index table is not added to the first image data.
The alpha value index table, i.e., the 255 value, is not added to the first image data to describe its alpha value channel data. The image quality is the same because of the color effect exhibited when the alpha value of the pixel is 255 as compared to when the alpha value is not included. Therefore, the alpha value need not be added.
When the alpha value is not equal to 255, step S73 is performed.
S73: an alpha value index table is added to the first image data.
The pixels containing the alpha channel will not behave the same as pixels not containing the alpha channel. It is therefore necessary to add this alpha value to the first image data to describe the alpha value channel data.
After the second image data is obtained in step S13, step S14 is performed.
And S14, compressing the second image data.
After the second image data processed by the alpha channel is obtained, the RGB components of the second image data are subjected to lossy compression, and the alpha value channel data are subjected to lossless compression.
Referring to fig. 9, fig. 9 is a schematic structural diagram of an embodiment of the image processing apparatus of the present application.
The image processing apparatus 100 described in the embodiment of the present application may be a computer, a mobile phone, a tablet computer, a server, or a smart wearable device. The image processing apparatus 100 may include a processor 110 and a memory 120.
The processor 110 is used to control the operation of the image Processing apparatus, and the processor 110 may also be referred to as a Central Processing Unit (CPU). The processor 110 may be an integrated circuit chip having signal processing capabilities. The processor 110 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 120 may include Random Access Memory (RAM), read Only Memory (ROM), flash memory, erasable Programmable Read Only Memory (EPROM), electrically Erasable Programmable Read Only Memory (EEPROM), registers, a hard disk, a removable disk, a CD-ROM, and so forth. Memory 120 may store program data, which may include, for example, a single instruction, or many instructions, and may be distributed over several different code segments, among different programs, and across multiple memories 120. The memory 120 may be coupled to the processor 110 such that the processor 110 can read information from, and write information to, the memory 120. Of course, the memory 120 may be integrated into the processor 110.
The processor 110 may be used to execute program data or instructions stored in the memory 120 to implement the methods provided by the image processing method embodiments and possible combinations in the present application.
Referring to fig. 10, fig. 10 is a schematic structural diagram of an embodiment of a computer-readable storage device according to the present application.
An embodiment of the computer-readable storage device of the present application includes a memory 210, and the memory 210 stores program data that, when executed, implements the method provided by any one of the embodiments and possible combinations of the image processing method of the present application.
The aforementioned computer-readable storage device may include: various computer readable storage devices such as a usb disk, a portable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and electronic devices such as a computer, a mobile phone, a notebook computer, a tablet computer, and a camera having the storage devices.
In summary, with the image processing method, the image processing apparatus and the computer readable storage apparatus of the present application, the data characteristics of the alpha channel data included in the image are fully analyzed before the image with the alpha channel data is compressed, and the alpha channel data of the image is correspondingly processed, such as deleted or integrated, so as to reduce the data volume for describing the alpha channel data. On the basis of ensuring the image quality, the bit number of the code is reduced, and the compression efficiency is improved.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules or units is only one type of logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are intended to be included within the scope of the present application.
Claims (10)
1. An image processing method, characterized by comprising:
acquiring first image data;
extracting alpha channel data in the first image data; wherein the alpha channel data is used for describing the transparency of the image;
preprocessing the first image data according to the alpha channel data to obtain second image data;
compressing the second image data;
wherein, the preprocessing the first image data according to the alpha channel data to obtain second image data comprises:
determining a color format of the first image data;
when the color format of the first image data is an index color format, updating a first color palette of the first image data according to the alpha channel data to obtain a second color palette;
replacing the first palette in the first image data with the second palette to obtain second image data;
wherein, the updating the first palette of the first image data according to the alpha channel data to obtain a second palette comprises:
unifying color data corresponding to pixels with alpha values of 0 in the first palette into color data corresponding to any pixel with alpha values of 0; reserving one of a plurality of indexes with alpha values of 0 in the first palette, and removing the rest indexes with alpha values of 0 to obtain the second palette; or
Deleting the alpha value which is greater than a first set threshold value in the first palette to obtain a second palette; or
Dividing an alpha value into a plurality of intervals, and determining a target interval in the plurality of intervals; unifying color data of pixels with color data difference smaller than a second set threshold value in pixels of the target interval corresponding to the alpha value in the first palette into a middle value of the color data of the pixels with the color data difference smaller than the second set threshold value; and unifying the alpha values of the pixels with the color data difference smaller than a second set threshold value into a middle value of the alpha values of the target interval to obtain the second palette.
2. The method of claim 1, wherein said deleting alpha values in said first palette that are greater than a first set threshold further comprises, before obtaining said second palette:
and setting palette indexes for the pixels in the first palette according to the order of the alpha values from small to large.
3. The method of claim 1, wherein said pre-processing said first image data according to said alpha channel data to obtain second image data comprises:
determining a color format of the first image data;
when the color format of the first image data is a true color format, generating an alpha value index table according to the alpha channel data;
describing the alpha channel data according to the alpha value index table to obtain the second image data.
4. The method of claim 3, wherein said generating an alpha value index table from said alpha channel data comprises:
judging whether the alpha values in the alpha channel data are completely equal or not;
and when the alpha values are not completely equal, counting the number of the unequal alpha values, and generating the alpha value index table according to the number of the unequal alpha values.
5. The method of claim 4, wherein said generating said alpha value index table based on said number of unequal alpha values comprises:
when the number of said unequal alpha values is less than or equal to 2 k Describing an index by using k bits to construct the alpha value index table;
wherein k is one of 1, 2, 3, 4, 5, 6 and 7.
6. The method of claim 3, wherein said generating an alpha value index table from said alpha channel data comprises:
judging whether the alpha values in the alpha channel data are completely equal;
and when the alpha values are completely equal, deleting the alpha channel data, and constructing the alpha value index table by using the alpha values.
7. The method of claim 6, wherein said describing said alpha channel data according to said alpha value index table, obtaining said second image data comprises:
and adding the alpha value index table into the first image data to obtain the second image data.
8. The method of claim 6, wherein said describing said alpha channel data according to said alpha value index table, obtaining said second image data comprises:
when the alpha value is 255, the alpha value index table is not added to the first image data to obtain the second image data.
9. An image processing apparatus comprising a memory for storing program data executable by a processor to implement a method according to any one of claims 1 to 8 and a processor.
10. A computer-readable storage means, storing program data executable by a processor to perform the method of any one of claims 1 to 8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US5883633A (en) * | 1997-04-15 | 1999-03-16 | Microsoft Corporation | Method and system of variable run length image encoding using sub-palette |
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| US6118427A (en) * | 1996-04-18 | 2000-09-12 | Silicon Graphics, Inc. | Graphical user interface with optimal transparency thresholds for maximizing user performance and system efficiency |
| US8571311B2 (en) * | 2011-12-15 | 2013-10-29 | Microsoft Corporation | Raster graphics image transcoding for file size reduction |
| CN102881026B (en) * | 2012-08-15 | 2015-01-07 | 大连理工大学 | Palette device and generation method for image with transparency information |
| CN103826028B (en) * | 2012-11-19 | 2017-08-25 | 腾讯科技（深圳）有限公司 | A kind of method and apparatus of Lossless Compression picture |
| CN103209326B (en) * | 2013-03-29 | 2017-04-12 | 惠州学院 | PNG (Portable Network Graphic) image compression method |
| CN104142924A (en) * | 2013-05-06 | 2014-11-12 | 中国移动通信集团福建有限公司 | Method and device for compressing flash picture format |
| US9395894B2 (en) * | 2013-11-06 | 2016-07-19 | Software Ag | System and method for browser side colorizing of icon images |
| GB2539488B8 (en) * | 2015-06-18 | 2020-08-19 | Gurulogic Microsystems Oy | Encoder, decoder and method employing palette utilization and compression |
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| US5883633A (en) * | 1997-04-15 | 1999-03-16 | Microsoft Corporation | Method and system of variable run length image encoding using sub-palette |
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