CN113920036A - Interactive relighting editing method based on RGB-D image - Google Patents
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Abstract
The invention discloses an interactive relighting editing method based on RGB-D images. Firstly, preprocessing an input image to obtain a shadowless reflectivity map, a shading map and a shadow map; segmenting an original RGB image by using a MaskRCNN algorithm, acquiring a segmentation mask of an object in a scene, and then acquiring a corresponding local depth map, a shadow-free reflectivity map and a shadow-free light and shade map; decomposing the unshaded light and shade map into a global and local illumination detail map and a spherical harmonic illumination map; respectively sampling and visualizing the global and local spherical harmonic illumination maps, and obtaining the adjusted global and local spherical harmonic illumination maps through interactive editing; and synthesizing the global and local RGB relighting images edited by the ambient light according to the global and local unshaded reflectivity maps, the adjusted spherical harmonic illumination map and the shadow map, and outputting the global and local RGB relighting images. The method can effectively, conveniently and intuitively realize the enhancement of the indoor complex scene image under the low-light condition.
Description
Technical Field
The invention relates to the technical field of image processing technology and computer graphics, in particular to an interactive relighting editing method based on RGB-D images.
Background
Illumination information is an important factor that contributes to the quality of a photograph, and the illumination of a photograph, especially the ambient light distribution, directly affects the visual quality of the photograph. Especially in indoor low light scenes, the shot pictures have complex ambient light, the shooting effect is difficult to be directly shown in front of people, and even under the shooting of professional photographers, the people also need to improve the illumination distribution of the environment through an additional artificial light source. However, since the real scene is complex, even professional photographers are difficult to achieve a good illumination effect through later editing, and in addition, they cannot achieve natural and real local illumination editing to achieve local detail enhancement of the scene. Therefore, it is significant to provide a simple, effective and convenient interactive illumination editing method for users.
Some existing methods for adding light again, such as simple light models using a linear light source, a point light source or a spotlight, are not suitable for complex scenes under real-time light conditions, although they can adjust the light in the image. It is also difficult to estimate the number, location and illumination intensity of the light sources accurately. Although some interactive methods for re-illuminating can overcome these disadvantages, because three-dimensional information is not used as input, a large amount of interactive operations are required to determine the spatial structure of the scene and the information such as the position, direction and intensity of the light source, and the overall and local illumination of the scene cannot be enhanced at the same time.
Disclosure of Invention
The embodiment of the application provides an interactive relighting editing method based on RGB-D images, and effectively solves the problem that in the prior art, the illumination of complex scene images under indoor low-light conditions is difficult to be effectively enhanced globally and locally conveniently and efficiently.
The embodiment of the application provides an interactive illumination editing method based on RGBD images, which comprises the following steps,
step 1, firstly, preprocessing an input RGBD image to obtain a shadowless reflectivity graph, a shading graph and a shadow graph;
step 2, decomposing the unshaded light and shade image in the step 1 into an illumination detail image and a spherical harmonic illumination image;
and 3, sampling and visualizing the spherical harmonic illumination map in the step 2, and finally obtaining the adjusted spherical harmonic illumination map through interactive editing.
And 4, synthesizing the RGB image edited by the ambient light according to the shadowless reflectivity graph, the adjusted spherical harmonic illumination graph and the shadow graph, and outputting the RGB image.
Preferably, the step 1 comprises the following substeps:
step 1.1, graying an original RGB image, filtering the grayed image by using a relative total variation model, and finally obtaining an image with removed texture;
step 1.2, optimizing the original rough depth map by combining the RGBD-Fusion method and the image with the removed texture in step 1.1 to obtain a fine depth map;
step 1.3, removing image shadows from the original RGB image by combining the shadow removal method of a single RGBD image and the fine depth map in the step 1.2, and finally obtaining a shadow map and a shadow-free image;
and step 1.4, carrying out intrinsic image decomposition on the shadowless image in the step 1.3 by using an intrinsic image decomposition method, and finally obtaining a shadowless reflectivity image and a shadowless bright-dark image.
Preferably, the step 2 comprises the following substeps:
step 2.1, segmenting the original RGB image in the step 1 by using a MaskRCNN algorithm to obtain a segmentation mask of an object in a scene;
step 2.2, performing pixel-by-pixel multiplication operation on the mask of the object and the fine depth map, the shadowless reflectivity map and the shadowless shading map to obtain the fine depth map, the shadowless reflectivity map and the shadowless shading map of the corresponding object;
step 2.3, respectively calculating corresponding normal graphs by using the fine depth map of the global scene and the fine depth map of the corresponding local scene, and normalizing the normal graphs;
step 2.4, converting the normalized normal map of step 2.3 into a normal map with a size ofN×3A normal vector matrix;
step 2.5, constructing the shadowless light and shade graph of the global scene and the shadowless light and shade graph of the corresponding local scene into a length ofNA column vector of (a);
step 2.6, obtaining spherical harmonic coefficient vectors of the global scene and the local scene by using a least square method:
wherein,his a spherical harmonic coefficient vector of length 9,Ais a spherical harmonic basis matrix and is characterized in that,Scolumn vectors that are unshaded light and dark maps;
step 2.7, respectively obtaining a spherical harmonic illumination map and an illumination detail map of a global scene and a spherical harmonic illumination map and an illumination detail map of a local scene by using the spherical harmonic coefficient vector, wherein the corresponding calculation method comprises the following steps:
wherein,L、Drespectively, the spherical harmonic illumination map and the illumination detail map,
。
preferably, the step 3 comprises the following substeps: step 3.1, rendering and expanding the spherical harmonic coefficient vector corresponding to the spherical harmonic map on a cube, and finally respectively obtaining the ambient light distribution maps of the global scene and the local scene;
step 3.2, manually using tools such as a brush and the like to draw and interact on the environment light distribution map respectively to adjust the intensity and distribution of illumination, and finally obtaining the edited global and local environment light distribution map;
and 3.3, obtaining the global harmonic coefficient vector of the edited ambient light distribution map, and performing re-rendering according to the spherical harmonic coefficient vector to obtain the adjusted global and local spherical harmonic illumination maps.
Preferably, in said step 3.3
Step 3.3.1, respectively calculating corresponding normal graphs by using the global fine depth map and the corresponding fine depth map of the local scene, and normalizing the normal graphs;
step 3.3.2, converting the normalized normal map of step 3.3.1 into a size ofN×3A normal vector matrix of (a);
step 3.3.3, calculating a spherical harmonic basis matrix corresponding to the normal vector matrix by utilizing a 2-order spherical harmonic basis function, wherein the size of the spherical harmonic basis matrix isN×9；
Step 3.3.4, the unshaded light and shade images of the whole scene and the corresponding unshaded light and shade images of the local scene are respectively constructed into the length of the unshaded light and shade images according to the sequence of the line main sequenceNA column vector of (a);
step 3.3.5, obtaining spherical harmonic coefficient vectors of the whole scene and the local scene by using a least square method:
wherein,his a spherical harmonic coefficient vector of length 9,Ais a spherical harmonic basis matrix and is characterized in that,Sis the edited ambient light profile vector.
Preferably, the method for calculating the RGB image after editing the ambient light synthesized in step 4 includes:
wherein,Ithe edited output RGB image for said ambient light,
in order to be the shadow map,
for the adjusted spherical harmonic illumination map,Ris the shadowless reflectivity map.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
in the embodiment of the application, an input RGB image and a corresponding depth image are preprocessed to obtain a shadow-free reflectance map, a shadow-free shading map and a shadow map, the shadow-free shading map is decomposed into an illumination detail map and a spherical harmonic illumination map, an adjusted spherical harmonic illumination map is finally obtained through an interactive editing method, and finally the RGB image edited by ambient light is synthesized according to the shadow-free reflectance map, the adjusted spherical harmonic illumination map and the shadow map and output. The invention preprocesses the input image, decomposes the light and shade image into an illumination detail image and a spherical harmonic illumination image, adjusts the spherical harmonic illumination image in a user interaction mode, correspondingly adjusts the shadow, and finally resynthesizes to obtain the image edited by the ambient light. The method estimates the ambient light in the image by combining with a depth map optimization algorithm, edits the ambient light in a user interaction mode and synthesizes the ambient light again, so that the ambient light condition of the image achieves the expected effect. The relighting editing method provided by the invention mainly aims at indoor complex scenes under various low-light conditions, and can be used for visually and effectively performing illumination editing through user interaction, so that relighting of global and local scenes of an image is realized, and meanwhile, the relighting editing method has better robustness for user input.
Drawings
In order to more clearly illustrate the technical solution in the present embodiment, the drawings needed to be used in the description of the embodiment will be briefly introduced below, and it is obvious that the drawings in the following description are one embodiment of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a general design flowchart of an interactive relighting editing method based on RGB-D images according to an embodiment of the present invention.
Fig. 2 is a graph of an image global relighting experiment result of the RGB-D image-based interactive relighting editing method provided in this embodiment.
Fig. 3 is a graph of an image local relighting experiment result of the RGB-D image-based interactive relighting editing method provided in this embodiment.
Detailed Description
For better understanding of the above technical solutions, the following detailed descriptions will be provided in conjunction with the drawings and the detailed description of the embodiments.
The invention provides an interactive relighting editing method based on RGB-D images, which mainly comprises the following steps:
step 1, firstly, preprocessing an input RGBD image to obtain a shadowless reflectivity graph, a shading graph and a shadow graph;
step 2, decomposing the unshaded light and shade image in the step 1 into an illumination detail image and a spherical harmonic illumination image;
and 3, sampling and visualizing the spherical harmonic illumination map in the step 2, and finally obtaining the adjusted spherical harmonic illumination map through interactive editing.
And 4, synthesizing the RGB image edited by the ambient light according to the shadowless reflectivity graph, the adjusted spherical harmonic illumination graph and the shadow graph, and outputting the RGB image.
The invention will be further described with reference to the accompanying drawings.
Referring to fig. 1 to fig. 3, the interactive relighting editing method based on RGB-D images provided in this embodiment mainly includes the following steps:
first, for an input resolution of
The RGB image and the corresponding depth map are preprocessed, grayed, and the grayscale image is filtered by using a relative total variation model, so that the image with the removed texture, namely the structure diagram, is finally obtained.
And (3) combining an RGBD (red, green and blue) polymerization method with the image with the removed texture, and performing depth map optimization on the originally input rough depth image to obtain a fine depth map.
The shadow removing method of a single RGBD image is combined with the fine depth map to remove the shadow of the original RGB image, so that a shadow map and a shadow-free image are obtained.
And decomposing the shadow-free image by using an intrinsic image decomposition algorithm to obtain a shadow-free reflectivity map and a shadow-free light and shade map.
And respectively decomposing the light and dark images into a corresponding global illumination detail image, a global spherical harmonic illumination image, a local illumination detail image and a local spherical harmonic illumination image based on the spherical harmonic illumination. The specific process is as follows:
segmenting the original RGB image in the step 1 by using a MaskRCNN algorithm to obtain a segmentation mask of an object in a scene;
carrying out pixel-by-pixel multiplication operation on the mask of the object and the fine depth map, the shadowless reflectivity map and the shadowless shading map to obtain the fine depth map, the shadowless reflectivity map and the shadowless shading map of the corresponding object;
respectively calculating corresponding normal maps by using the fine depth map of the global scene and the fine depth map of the corresponding local scene, and normalizing the normal maps; the global scene is to perform overall operation on the whole input image, and the local scene is to segment objects in the scene through Mask-RCNN and to operate the objects in the single segmented scene.
Converting the normalized normal map to a size ofN×3A normal vector matrix of (a);
constructing the unshaded light and shade graph of the global scene and the unshaded light and shade graph of the corresponding local scene into the light and shade graph with the length ofNA column vector of (a);
obtaining spherical harmonic coefficient vectors of a global scene and a local scene by using a least square method:
wherein,his a spherical harmonic coefficient vector of length 9,Ais a spherical harmonic basis matrix and is characterized in that,Sthe edited vector of the ambient light distribution map is obtained;
respectively obtaining a spherical harmonic illumination map and an illumination detail map of a global scene and a spherical harmonic illumination map and an illumination detail map of a local scene by using the spherical harmonic coefficient vector, wherein the corresponding calculation method comprises the following steps:
wherein,L、Drespectively, the spherical harmonic illumination map and the illumination detail map,
。
and editing the global spherical harmonic illumination map and the local spherical harmonic illumination map respectively in a user interaction mode to obtain the global spherical harmonic illumination map and the local spherical harmonic illumination map after the ambient light is adjusted. The specific process is as follows:
rendering and expanding the spherical harmonic coefficient vectors corresponding to the spherical harmonic illumination map on a cube, and finally obtaining the ambient light distribution maps of the global scene and the local scene respectively;
manually drawing and interacting the environment light distribution map by using tools such as a brush and the like to adjust the intensity and distribution of illumination, and finally obtaining the edited global and local environment light distribution map; the image to be edited is an unfolded hexahedral box, illumination in different directions is realized on different surfaces through white dots or lines on the picture, namely, a light source is added, the number and the thickness of the white lines represent the intensity of the illumination, for example, the white lines are drawn below the unfolded cubic box to show that a light source is added in front of the scene, and the interaction mode is simple and effective.
And 6.3, obtaining the global harmonic coefficient vector of the edited ambient light distribution map, and performing re-rendering according to the spherical harmonic coefficient vector to obtain the adjusted global and local spherical harmonic illumination maps.
And 7, synthesizing the corresponding global and local shadowless reflectivity maps, the adjusted spherical harmonic illumination map and the shadow map to finally obtain the RGB image edited by the ambient light, wherein the general calculation method for synthesizing the global and local reflectivity maps comprises the following steps:
wherein,Ithe edited output RGB image for said ambient light,
the shadow map, i.e. the artwork,
for the adjusted spherical harmonic illumination map,Ris the shadowless reflectivity map.
The interactive relighting editing method based on the RGB-D image can effectively separate the shadow map from the spherical harmonic illumination map, and is beneficial to efficient expansion of the subsequent relighting process.
Fig. 2 shows two sets of experimental results of the present invention for global image relighting, where (a) is the input original image, and (b), (c), (d), and (e) respectively show the relighting above, to the left, in front of, and on the whole, thereby achieving the result of relighting the scene. As can be seen from the figure, the method of the invention can effectively realize global relighting in a certain direction.
Fig. 3 shows two sets of results of global relighting and local relighting performed on a complex indoor scene according to the present invention, where (a) is an input original image, and (b), (d), (c), and (e) respectively represent global and local relighting performed on the scene, and it can be seen from the figure that (b) and (d) achieve a considerable global relighting effect, and (c) and (e) not only achieve a good local relighting of the scene but also enhance the local details of the scene.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to examples, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (6)
1. An interactive relighting editing method based on RGB-D images is characterized by comprising the following steps:
step 1, firstly, preprocessing an input RGBD image to obtain a shadowless reflectivity graph, a shading graph and a shadow graph;
step 2, decomposing the unshaded light and shade image in the step 1 into an illumination detail image and a spherical harmonic illumination image;
step 3, sampling and visualizing the spherical harmonic illumination map in the step 2, and finally obtaining an adjusted spherical harmonic illumination map through interactive editing;
and 4, synthesizing the RGB image edited by the ambient light according to the shadowless reflectivity graph, the adjusted spherical harmonic illumination graph and the shadow graph, and outputting the RGB image.
2. An interactive relighting editing method based on RGB-D images as claimed in claim 1, characterized in that said step 1 comprises the following sub-steps:
step 1.1, graying an original RGB image, filtering the grayed image by using a relative total variation model, and finally obtaining an image with removed texture;
step 1.2, optimizing the original rough depth map by combining the RGBD-Fusion method and the image with the removed texture in step 1.1 to obtain a fine depth map;
step 1.3, removing image shadows from the original RGB image by combining the shadow removal method of a single RGBD image and the fine depth map in the step 1.2, and finally obtaining a shadow map and a shadow-free image; and step 1.4, carrying out intrinsic image decomposition on the shadowless image in the step 1.3 by using an intrinsic image decomposition method, and finally obtaining a shadowless reflectivity image and a shadowless bright-dark image.
3. The RGB-D image-based interactive relighting editing method as recited in claim 2, wherein the step 2 includes the sub-steps of:
step 2.1, segmenting the original RGB image in the step 1 by using a MaskRCNN algorithm to obtain a segmentation mask of an object in a scene;
step 2.2, performing pixel-by-pixel multiplication operation on the mask of the object and the fine depth map, the shadowless reflectivity map and the shadowless shading map to obtain the fine depth map, the shadowless reflectivity map and the shadowless shading map of the corresponding object;
step 2.3, respectively calculating corresponding normal graphs by using the fine depth map of the global scene and the fine depth map of the corresponding local scene, and normalizing the normal graphs;
step 2.4, converting the normalized normal map of step 2.3 into a normal map with a size ofN×3A normal vector matrix of (a);
step 2.5, constructing the shadowless light and shade graph of the global scene and the shadowless light and shade graph of the corresponding local scene into a length ofNA column vector of (a);
step 2.6, obtaining spherical harmonic coefficient vectors of the global scene and the local scene by using a least square method:
wherein,his a spherical harmonic coefficient vector of length 9,Ais a spherical harmonic basis matrix and is characterized in that,Sthe edited vector of the ambient light distribution map is obtained;
step 2.7, respectively obtaining a spherical harmonic illumination map and an illumination detail map of a global scene and a spherical harmonic illumination map and an illumination detail map of a local scene by using the spherical harmonic coefficient vector, wherein the corresponding calculation method comprises the following steps:
wherein,L、Drespectively, the spherical harmonic illumination map and the illumination detail map,
。
4. the RGB-D image-based interactive relighting editing method as recited in claim 3, wherein the step 3 includes the steps of:
step 3.1, rendering and expanding the spherical harmonic coefficient vector corresponding to the spherical harmonic map on a cube, and finally respectively obtaining the ambient light distribution maps of the global scene and the local scene;
step 3.2, manually using tools such as a brush and the like to draw and interact on the environment light distribution map respectively to adjust the intensity and distribution of illumination, and finally obtaining the edited global and local environment light distribution map;
and 3.3, obtaining the global harmonic coefficient vector of the edited ambient light distribution map, and performing re-rendering according to the spherical harmonic coefficient vector to obtain the adjusted global and local spherical harmonic illumination maps.
5. An interactive relighting editing method based on RGB-D images as claimed in claim 4, characterized in that said step 3.3 comprises the following sub-steps:
step 3.3.1, respectively calculating corresponding normal graphs by using the global fine depth map and the corresponding fine depth map of the local scene, and normalizing the normal graphs;
step 3.3.2, converting the normalized normal map of step 3.3.1 into a size ofN×3A normal vector matrix of (a);
step 3.3.3, calculating a spherical harmonic basis matrix corresponding to the normal vector matrix by utilizing a 2-order spherical harmonic basis function, wherein the size of the spherical harmonic basis matrix isN×9；
Step 3.3.4, the unshaded light and shade images of the whole scene and the corresponding unshaded light and shade images of the local scene are respectively constructed into the light and shade images with the length ofNA column vector;
step 3.3.5, obtaining spherical harmonic coefficient vectors of the whole scene and the local scene by using a least square method:
wherein,his a spherical harmonic coefficient vector of length 9,Ais a spherical harmonic basis matrix and is characterized in that,Sis the edited ambient light profile vector.
6. The RGB-D image-based interactive relighting editing method as claimed in claim 5, wherein the computing method for synthesizing the RGB image edited by the ambient light in the step 4 is:
wherein,Ithe edited output RGB image for said ambient light,
in order to be the shadow map,
for the adjusted spherical harmonic illumination map,Ris the shadowless reflectivity map.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114581611A (en) * | 2022-04-28 | 2022-06-03 | 阿里巴巴（中国）有限公司 | Virtual scene construction method and device |
| CN115375827A (en) * | 2022-07-21 | 2022-11-22 | 荣耀终端有限公司 | Illumination estimation method and electronic equipment |
| CN115546010A (en) * | 2022-09-21 | 2022-12-30 | 荣耀终端有限公司 | Image processing method and electronic device |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447906A (en) * | 2015-11-12 | 2016-03-30 | 浙江大学 | Method for calculating lighting parameters and carrying out relighting rendering based on image and model |
| CN106127818A (en) * | 2016-06-30 | 2016-11-16 | 珠海金山网络游戏科技有限公司 | A kind of material appearance based on single image obtains system and method |
| CN109886906A (en) * | 2019-01-25 | 2019-06-14 | 武汉大学 | A kind of real-time dim light video enhancement method and system of details sensitivity |
| CN110033055A (en) * | 2019-04-19 | 2019-07-19 | 中共中央办公厅电子科技学院(北京电子科技学院) | A kind of complex object image weight illumination method based on the parsing of semantic and material with synthesis |
| CN110570496A (en) * | 2019-08-26 | 2019-12-13 | 武汉大学 | RGBD image environment light editing method and system based on spherical harmonic illumination |
| CN111127377A (en) * | 2019-12-20 | 2020-05-08 | 湖北工业大学 | Weak light enhancement method based on multi-image fusion Retinex |
| US10665011B1 (en) * | 2019-05-31 | 2020-05-26 | Adobe Inc. | Dynamically estimating lighting parameters for positions within augmented-reality scenes based on global and local features |
| CN113240622A (en) * | 2021-03-12 | 2021-08-10 | 清华大学 | Human body scene image intrinsic decomposition and relighting method and device |
-
2021
- 2021-12-14 CN CN202111520120.0A patent/CN113920036A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447906A (en) * | 2015-11-12 | 2016-03-30 | 浙江大学 | Method for calculating lighting parameters and carrying out relighting rendering based on image and model |
| CN106127818A (en) * | 2016-06-30 | 2016-11-16 | 珠海金山网络游戏科技有限公司 | A kind of material appearance based on single image obtains system and method |
| CN109886906A (en) * | 2019-01-25 | 2019-06-14 | 武汉大学 | A kind of real-time dim light video enhancement method and system of details sensitivity |
| CN110033055A (en) * | 2019-04-19 | 2019-07-19 | 中共中央办公厅电子科技学院(北京电子科技学院) | A kind of complex object image weight illumination method based on the parsing of semantic and material with synthesis |
| US10665011B1 (en) * | 2019-05-31 | 2020-05-26 | Adobe Inc. | Dynamically estimating lighting parameters for positions within augmented-reality scenes based on global and local features |
| CN110570496A (en) * | 2019-08-26 | 2019-12-13 | 武汉大学 | RGBD image environment light editing method and system based on spherical harmonic illumination |
| CN111127377A (en) * | 2019-12-20 | 2020-05-08 | 湖北工业大学 | Weak light enhancement method based on multi-image fusion Retinex |
| CN113240622A (en) * | 2021-03-12 | 2021-08-10 | 清华大学 | Human body scene image intrinsic decomposition and relighting method and device |
Non-Patent Citations (1)
| Title |
|---|
| ADITYA ARORA 等: "Low Light Image Enhancement via Global and Local Context Modeling", 《ARXIV：2101.00850V1》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114581611A (en) * | 2022-04-28 | 2022-06-03 | 阿里巴巴（中国）有限公司 | Virtual scene construction method and device |
| CN114581611B (en) * | 2022-04-28 | 2022-09-20 | 阿里巴巴（中国）有限公司 | Virtual scene construction method and device |
| CN115375827A (en) * | 2022-07-21 | 2022-11-22 | 荣耀终端有限公司 | Illumination estimation method and electronic equipment |
| CN115375827B (en) * | 2022-07-21 | 2023-09-15 | 荣耀终端有限公司 | Illumination estimation method and electronic equipment |
| CN115546010A (en) * | 2022-09-21 | 2022-12-30 | 荣耀终端有限公司 | Image processing method and electronic device |
| CN115546010B (en) * | 2022-09-21 | 2023-09-12 | 荣耀终端有限公司 | Image processing method and electronic equipment |
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