Image processing method and device, electronic equipment, storage medium and program product

Abstract

Embodiments of the present disclosure disclose an image processing method and device, electronic equipment, storage medium and program product. The method comprises: obtaining a first two-dimensional image, the first two-dimensional image being obtained by performing a preset two-dimensional image processing on a two-dimensional rendering image of a first three-dimensional model in a three-dimensional scene; obtaining first texture detail information of the first three-dimensional model in the three-dimensional scene; and obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first texture detail information and the first two-dimensional image. The technical solution of the embodiments of the present disclosure realizes the introduction of lossless original texture information of a three-dimensional model into the processing logic of a post-processing process without changing the original two-dimensional image quality optimization link, and achieves the technical effects of improving the texture completeness of an output image and making the picture performance highly consistent with the original design expectation of a three-dimensional model, which can directly adapt to the fine image quality requirements of various media content production scenes such as game rendering and film post-production.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more particularly to an image processing method, apparatus, electronic device, storage medium, and program product. Background Technology

[0002] In current media content production scenarios such as game rendering and film and television post-production, after the 3D model completes the 3D scene construction and rendering, the generated 2D rendered image often needs to enter an independent 2D image processing link to complete image quality optimization. This type of pixel-based processing flow is the most widely used image processing solution in the industry.

[0003] However, this type of processing mode, which relies solely on two-dimensional image pixel data for adjustments, typically erases the fine textures of the model's surface during image quality optimization, ultimately leading to the loss of model texture details and distortion of image information in the processed image. Therefore, there is an urgent need to propose an image processing method to compensate for the loss of texture details caused by existing pixel-level image processing. Summary of the Invention

[0004] This invention provides an image processing method, apparatus, electronic device, storage medium, and program product to introduce the original texture information of a 3D model into the post-processing workflow without altering the original 2D image quality optimization link. This achieves the technical effect of improving the texture integrity of the output image and ensuring that the image performance closely matches the original design expectations of the 3D model. It can directly adapt to the refined image quality requirements of various media content production scenarios such as game rendering and film post-production.

[0005] According to one aspect of the present invention, an image processing method is provided, the method comprising: Obtain a first two-dimensional image, which is a two-dimensional rendered image of the first three-dimensional model in a three-dimensional scene obtained through preset two-dimensional image processing; Obtain the first texture detail information of the first three-dimensional model in the three-dimensional scene; Based on the first texture detail information and the first two-dimensional image, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

[0006] According to another aspect of the present invention, an image processing apparatus is provided, the apparatus comprising: The first module is used to acquire a first two-dimensional image, which is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene. The second module is used to obtain the first texture detail information of the first three-dimensional model in the three-dimensional scene; The third module is used to obtain a second two-dimensional image corresponding to the first two-dimensional image based on the first texture detail information and the first two-dimensional image.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: One or more processors; Storage device for storing one or more programs. When one or more programs are executed by one or more processors, the one or more processors implement any of the image processing methods described in the embodiments of this disclosure.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute any of the image processing methods of the present invention.

[0009] According to another aspect of the present disclosure, a computer program product is provided, which, when executed by a processor, implements any of the image processing methods described in the embodiments of the present disclosure.

[0010] The technical solution of this disclosure involves obtaining a first two-dimensional image by acquiring a two-dimensional rendered image of a first three-dimensional model in a three-dimensional scene and processing it using a preset two-dimensional image processing method. Lossless original texture details are directly extracted from the three-dimensional scene data of the first three-dimensional model to obtain first texture detail information of the first three-dimensional model in the three-dimensional scene. Based on the first texture detail information, the missing texture details in the first two-dimensional image are supplemented to obtain a second two-dimensional image corresponding to the first two-dimensional image. This technical solution solves the technical problem that existing image processing methods, which rely solely on two-dimensional image pixel processing, cannot preserve the original texture features of the model and are prone to erasing texture details. It achieves the processing logic of introducing lossless original texture information of the three-dimensional model into the post-processing flow without altering the original two-dimensional image quality optimization link. This results in improved texture integrity of the output image and a high degree of consistency between the image performance and the original design expectations of the three-dimensional model, directly adapting to the refined image quality requirements of various media content production scenarios such as game rendering and film post-production.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic flowchart of an image processing method provided in an embodiment of the present disclosure; Figure 2 This is a schematic flowchart of an image processing method provided in an embodiment of the present disclosure; Figure 3 This is a schematic flowchart of an image processing method provided in an embodiment of the present disclosure; Figure 4 This is a schematic flowchart of an image processing method provided in an embodiment of the present disclosure; Figure 5 An example diagram of a two-dimensional character image provided in an embodiment of this disclosure; Figure 6 This is an example diagram of the clothing model area of ​​a virtual character model provided in this disclosure. Figure 7 This is an example diagram showing the texture details of a clothing model area for a virtual character model provided in this disclosure. Figure 8 An example image of a processed two-dimensional character image provided in this disclosure; Figure 9 This is a schematic diagram of the structure of an image processing apparatus provided in an embodiment of the present disclosure; Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0017] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0018] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0019] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0020] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0021] Figure 1This is a flowchart illustrating an image processing method provided in an embodiment of the present disclosure. This embodiment is applicable to adding texture details to a 2D rendered image of a 3D model, and is particularly suitable for scenarios where the texture details of a 2D rendered image of a 3D model are missing. The method can be executed by an image processing device, which can be implemented in hardware and / or software, and can be configured in electronic devices such as computers or servers. Figure 1 As shown, the method in this embodiment includes: S110. Obtain a first two-dimensional image, wherein the first two-dimensional image is obtained by processing a preset two-dimensional image of the first three-dimensional model in a three-dimensional scene through a two-dimensional rendering image.

[0022] The first two-dimensional image can be understood as a two-dimensional image obtained by performing preset two-dimensional image processing on a two-dimensional image rendered from a three-dimensional model in a three-dimensional scene. The first three-dimensional model can be understood as a three-dimensional mesh model with associated texture materials in a three-dimensional scene. There can be one or more first three-dimensional models. A three-dimensional mesh model is a three-dimensional model with a geometric topological structure, composed of three basic elements: vertices, edges, and faces. Two-dimensional image processing can be understood as preset operations performed on the rendered image output from the three-dimensional model in a three-dimensional scene using two-dimensional image processing tools. Two-dimensional image processing includes image compositing processing. In this embodiment, the two-dimensional image processing can be set according to actual needs and is not specifically limited here. In one case, the two-dimensional image processing at least includes operations to remove the texture details of the first three-dimensional model from the two-dimensional rendered image. For example, image noise reduction processing, image blurring processing, image downsampling processing, etc.

[0023] There are several ways to obtain the first 2D image, and none are limited here. In one scenario, a 2D rendered image of the first 3D model in a 3D scene is obtained; this rendered image undergoes preset 2D image processing to obtain the processed 2D image, which is the first 2D image. In another scenario, a 2D rendered image of the first 3D model in a 3D scene is obtained, and at least one image element is added to this rendered image. The image element does not obscure or cover the display area of ​​the first 3D model in the 2D rendered image and does not interfere with the model's outline, texture, or other visual information. The addition operation can be completed through layer overlay and alpha mask blending. The resulting 2D image after adding the element is the first 2D image.

[0024] S120. Obtain the first texture detail information of the first three-dimensional model in the three-dimensional scene.

[0025] The first texture detail information can be understood as the texture detail information inherent in the first 3D model itself. Specifically, the texture detail information of the first 3D model in the 3D scene is extracted to obtain the first texture detail information of the first 3D model. In this embodiment, extracting texture detail information directly from the 3D model avoids the texture loss that may be introduced in the 2D rendering and 2D image processing stages, obtains the original full texture data of the model, eliminates the need for complex reverse reconstruction calculations, reuses the model's built-in texture coordinate mapping and material parameters, accurately matches the detail completion requirements of the 2D image, and effectively improves the texture restoration accuracy and processing efficiency of the image.

[0026] Because the image obtained after two-dimensional image processing loses model texture details, the image information is distorted. In this embodiment of the disclosure, the first texture detail information of the first three-dimensional model in the three-dimensional scene is directly obtained because the three-dimensional scene stores the original and complete texture detail information of the three-dimensional model. The data is complete and undistorted, and the accuracy is higher. It can effectively make up for the texture loss defects caused by two-dimensional pixel-level processing and ensure the authenticity and integrity of the final image texture restoration.

[0027] In this embodiment of the disclosure, obtaining the first texture detail information of the first three-dimensional model in the three-dimensional scene may include: obtaining the model texture map associated with the first three-dimensional model in the three-dimensional scene, and the coordinate mapping relationship between the pixels of the model texture map and the vertices of the surface of the first three-dimensional model; and obtaining the first texture detail information of the first three-dimensional model based on the coordinate mapping relationship and the model texture map.

[0028] In this context, a model texture map can be understood as a two-dimensional image pre-bound to the first 3D model, carrying the model's surface color and texture details. A model texture map can include one of the following: diffuse base color map, normal bump map, roughness map, metallicity map, or transparency map. Different types of maps carry surface details in their respective dimensions, collectively forming a complete set of texture information. The coordinate mapping relationship between the pixels of the model texture map and the vertices of the first 3D model surface is called the texture coordinate (UV) mapping relationship. This mapping relationship allows the model texture map to be accurately fitted onto the irregular curved surfaces of the 3D model, thus ensuring correct texture display and supporting the extraction of high-fidelity, low-loss first texture detail information. The coordinate mapping relationship can be used to determine the corresponding pixel point in the 2D texture map for each vertex on the 3D model.

[0029] It should be noted that the UV mapping relationship is an orthogonal coordinate system defined in a two-dimensional texture space. It is used to establish a one-to-one correspondence between the vertices of the 3D model surface and the pixels of the 2D texture map. The U-axis corresponds to the horizontal direction of the 2D texture map, and the V-axis corresponds to the vertical direction of the 2D texture map. This mapping relationship can achieve unbiased positioning of any surface point of the 3D model to the corresponding texture pixel, thereby avoiding problems such as stretching, misalignment, and region crosstalk during texture mapping.

[0030] In this embodiment of the disclosure, obtaining the first texture detail information of the first three-dimensional model based on the coordinate mapping relationship and the model texture map may include: processing the color value of each pixel in the model texture map into a structured pixel array that can be read by coordinate index according to row and column order; establishing an index correspondence between the vertices of the three-dimensional model surface and the texture pixels based on the coordinate mapping relationship; and completing the surface texture information through vertex sampling and patch interpolation to obtain the first texture detail information of the first three-dimensional model.

[0031] S130. Based on the first texture detail information and the first two-dimensional image, obtain a second two-dimensional image corresponding to the first two-dimensional image.

[0032] The second two-dimensional image can be understood as a two-dimensional image obtained by adding first texture detail information to the first two-dimensional image. In this embodiment, the second two-dimensional image is an image that satisfies two-dimensional image processing and completes the texture detail information. Specifically, the texture detail information is mapped and aligned to the first two-dimensional image to complete the missing texture details, thereby obtaining a second two-dimensional image corresponding to the first two-dimensional image.

[0033] The technical solution of this disclosure involves obtaining a first two-dimensional image by acquiring a two-dimensional rendered image of a first three-dimensional model in a three-dimensional scene and processing it using a preset two-dimensional image processing method. Lossless original texture details are directly extracted from the three-dimensional scene data of the first three-dimensional model to obtain first texture detail information of the first three-dimensional model in the three-dimensional scene. Based on the first texture detail information, the missing texture details in the first two-dimensional image are supplemented to obtain a second two-dimensional image corresponding to the first two-dimensional image. This technical solution solves the technical problem that existing image processing methods, which rely solely on two-dimensional image pixel processing, cannot preserve the original texture features of the model and are prone to erasing texture details. It achieves the processing logic of introducing lossless original texture information of the three-dimensional model into the post-processing flow without altering the original two-dimensional image quality optimization link. This results in improved texture integrity of the output image and a high degree of consistency between the image performance and the original design expectations of the three-dimensional model, directly adapting to the refined image quality requirements of various media content production scenarios such as game rendering and film post-production.

[0034] Figure 2 This is a schematic flowchart illustrating another image processing method provided in this embodiment. The technical solution of this embodiment can be combined with other embodiments; for the same or related parts, they can be described in conjunction with the descriptions of other embodiments, and will not be repeated here. Figure 2 As shown, the method in this embodiment may specifically include: S210. Obtain a first two-dimensional image, wherein the first two-dimensional image is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene; the first three-dimensional model includes multiple first local regions.

[0035] The first local region can be understood as multiple independent sub-regions divided from the 3D surface of the first 3D model according to geometric features and texture attributes. Each sub-region has a continuous surface topology and can correspond to an independent texture region on a texture map. Different first local regions in the model correspond to different texture details. In one case, the first local region can be divided according to the component structure of the first 3D model. For example, taking a car model as an example, it can be divided into multiple first local regions corresponding to the body shell, wheels, windows, and headlights. As another example, taking a teapot model as an example, it can be divided into multiple first local regions corresponding to the body, spout, handle, lid, and bottom of the teapot.

[0036] S220. Determine the second local region in the first two-dimensional image that corresponds to each of the first local regions.

[0037] The second local region can be understood as a local region in the first two-dimensional image that corresponds to the first local region. The number of second local regions is the same as the number of first local regions.

[0038] In one scenario, a rendering coordinate mapping method can be used to determine the second local region corresponding to each first local region in the first two-dimensional image. Specifically, a projection matrix for three-dimensional rendering is used to project the three-dimensional vertex coordinates of the first local region onto the pixel coordinate system of the second two-dimensional image to determine the corresponding second local region.

[0039] In another scenario, a UV-reverse mapping method can be used to determine the second local region in the first two-dimensional image corresponding to each first local region. Specifically, through UV coordinate mapping, the texture pixel positions corresponding to the first local regions are inversely associated with the corresponding regions in the first two-dimensional image, thus determining the second local region corresponding to the first local region.

[0040] S230. Based on the model texture data of the first three-dimensional model in the three-dimensional scene and each of the second local regions, obtain the second texture detail information corresponding to each of the second local regions.

[0041] The model texture data can include model texture maps and the coordinate mapping relationship between the pixels of the model texture maps and the vertices of the first 3D model surface. The second texture detail information can be understood as the texture detail information in the image region corresponding to the first local region in the first 3D model within the first 2D image. In short, the second texture detail information is local image texture information.

[0042] In this embodiment, a model texture map associated with the first 3D model in a 3D scene is obtained, and the coordinate mapping relationship between the pixels of the model texture map and the vertices of the first 3D model surface is obtained. Then, based on the model texture map and the coordinate mapping relationship, second texture detail information corresponding to each second local region can be obtained. Specifically, for each second local region, each pixel in the second local region is traversed to determine the target vertex on the surface of the first 3D model corresponding to the pixel. Based on the coordinate mapping relationship, the corresponding texture block on the model texture map is determined according to the coordinates corresponding to the target vertex. The texture block is sampled, and pixel information is extracted to obtain the second texture detail information corresponding to the second local region.

[0043] S240. Based on the first two-dimensional image and each of the second texture detail information, obtain a second two-dimensional image corresponding to the first two-dimensional image.

[0044] Specifically, for each piece of second texture detail information, a second local region in the first two-dimensional image corresponding to the second texture detail information is determined, and the second texture detail information is mapped to the second local region. When the first two-dimensional image has each piece of second texture detail information added, the first two-dimensional image with the added second texture detail information can be used as the second two-dimensional image.

[0045] For example, the first local region in the first three-dimensional model includes local region A1 and local region A2. The second local region in the first two-dimensional image includes local region B1 and local region B2. Local regions A1 and B1 correspond to each other, and local regions A2 and B2 correspond to each other. Texture information is extracted from local region A1 to obtain second texture information C1 corresponding to local region B1, and texture information is extracted from local region A2 to obtain second texture information C2 corresponding to local region B2. The second texture information C1 and the second texture information C2 are respectively superimposed onto the corresponding second local regions B1 and B2 in the first two-dimensional image.

[0046] The technical solution of this disclosure embodiment determines the second local region in the first two-dimensional image corresponding to each of the first local regions; obtains the second texture detail information corresponding to each of the second local regions based on the model texture data of the first three-dimensional model in the three-dimensional scene and each of the second local regions; and obtains the second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each of the second texture detail information, thereby realizing texture completion processing of the corresponding image region in the first two-dimensional image with the local region of the three-dimensional model surface as the granularity.

[0047] Figure 3 This is a schematic flowchart illustrating another image processing method provided in this embodiment. The technical solution of this embodiment can be combined with other embodiments; for the same or related parts, they can be described in conjunction with the descriptions of other embodiments, and will not be repeated here. Figure 3 As shown, the method in this embodiment may specifically include: S310. Obtain a first two-dimensional image, wherein the first two-dimensional image is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene; the first three-dimensional model includes multiple first local regions.

[0048] S320. Determine the second local region in the first two-dimensional image that corresponds to each of the first local regions.

[0049] S330. Based on the model texture data of the first three-dimensional model in the three-dimensional scene and each of the second local regions, obtain the second texture detail information corresponding to each of the second local regions.

[0050] S340. Obtain a layer template corresponding to the first two-dimensional image, wherein the layer template includes multiple layers.

[0051] The layer template can be understood as a template used to add texture details to a first two-dimensional image. It is generated based on the outer contour of the first two-dimensional image. The layer template includes multiple preset independent layers, which are used to carry different second texture detail information respectively. All layers are aligned with the size and coordinates of the first two-dimensional image. The UV channels of different layers are independent of each other. In the embodiments of this disclosure, the layer template supports adding texture details to the corresponding layers to avoid texture aliasing interference. The layer template has at least two layers. The number of layers in the layer template and the number of second local regions can be the same or different. For example, if there are 3 second local regions, the layer template can also have 3 layers. Or, if there are 3 second local regions, the layer template can have 2 or 4 layers.

[0052] In one scenario, the layer template can be constructed based on the image attributes of a first two-dimensional image; these image attributes include at least the image size. Specifically, obtaining the layer template corresponding to the first two-dimensional image can include: creating independent layers corresponding to each second local region in the first two-dimensional image based on the size of the first two-dimensional image. Layer templates can then be generated based on these layers.

[0053] In another scenario, the layer template can be obtained based on an existing layer template containing multiple layers. Specifically, a layer template can be selected from existing layer templates. Thus, a layer template corresponding to the first two-dimensional image can be obtained based on the selected layer template. There are several ways to obtain a layer template corresponding to the first two-dimensional image based on the selected layer template. For example, the selected layer template can be used as the layer template corresponding to the first two-dimensional image. Alternatively, the selected layer template can be adjusted, and the adjusted layer template can be used as the layer template corresponding to the first two-dimensional image. Optionally, adjusting the selected layer template can include one of the following: adding a layer to the layer template, deleting a layer from the layer template, or adjusting the size of the layers in the layer template.

[0054] S350. Determine the layer corresponding to each of the second texture detail information, and add the corresponding second texture detail information to each of the layers.

[0055] In one scenario, the layer template is pre-divided into sub-layers according to the spatial region of the first two-dimensional image, with each layer corresponding to an independent region within the image. The distribution area of ​​each second texture detail information in the first two-dimensional image is determined. Layers matching the corresponding regions in the layer template are then identified, i.e., the layers corresponding to each second texture detail information are determined. Subsequently, the corresponding second texture detail information can be added to each of these layers to ensure that texture information from different regions of the 3D model is added to the layers corresponding to the image regions of the first two-dimensional image.

[0056] In another scenario, each piece of second texture detail information corresponds to a semantic tag, and the layer template is set with the corresponding semantic attributes. Based on the semantic tag corresponding to the second texture detail information, the corresponding layer in the layer template is determined, thereby identifying the layer corresponding to each piece of second texture detail information.

[0057] In this embodiment of the disclosure, a layer is associated with a first local region. In one case, there is a one-to-one correspondence between layers and first local regions. That is, one layer corresponds to one first local region. In another case, one layer corresponds to at least two first local regions. Determining the layer corresponding to each of the second texture detail information may include: determining the first local region corresponding to the second texture detail information, and using the layer corresponding to the first local region as the layer corresponding to the second texture detail information.

[0058] Specifically, based on the correspondence between the second texture detail information and the first local region, the first local region corresponding to the second texture detail information is determined. Based on the correspondence between the first local region and layers in the layer template, the layer corresponding to the first local region is determined. The layer corresponding to the first local region is then used as the layer corresponding to the second texture detail information.

[0059] S360. Based on the first two-dimensional image and each processed layer, obtain a second two-dimensional image corresponding to the first two-dimensional image.

[0060] In one scenario, a first texture layer image of the first two-dimensional image is obtained based on each of the processed layers. The first texture layer image is then added onto the first two-dimensional image to obtain a second two-dimensional image corresponding to the first two-dimensional image. The first texture layer image can be understood as an image generated by overlaying the processed layers. In another scenario, the processing order of the processed layers is determined, and the processed layers are added sequentially to the first two-dimensional image according to the processing order to obtain the second two-dimensional image.

[0061] In this embodiment of the disclosure, obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each processed layer may include: obtaining alpha channel information corresponding to each processed layer; the alpha channel information is used to characterize the alpha channel value of each pixel in the processed layer; and obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the alpha channel information corresponding to each processed layer.

[0062] Obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the alpha channel information corresponding to each processed layer may include: obtaining a first texture layer image based on each processed layer; obtaining alpha channel information corresponding to the first texture layer image based on the alpha channel information corresponding to each processed layer; and obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first texture layer image, the first two-dimensional image, and the alpha channel information corresponding to the first texture layer image. The alpha channel information corresponding to the first texture layer image is used to characterize the alpha channel value of each pixel in the first texture layer image. Obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first texture layer image, the first two-dimensional image, and the alpha channel information corresponding to the first texture layer image may include: obtaining a second two-dimensional image corresponding to the first two-dimensional image based on a texture mapping relationship, the first texture layer image, the first two-dimensional image, and the alpha channel information corresponding to the first texture layer image.

[0063] Optionally, a second two-dimensional image corresponding to the first two-dimensional image can be obtained using the following formula based on the texture mapping relationship, the first texture layer image, the first two-dimensional image, and the alpha channel information corresponding to the first texture layer image: ; in, It can represent the pixel coordinates of a second two-dimensional image. The output pixel values ​​generated by the fusion are shown. T1 can represent the first texture layer image. It can represent the pixel coordinates in the first texture layer image. The alpha channel value at that location. It can represent texture coordinates determined by the projection transformation matrix. The pixel values ​​sampled from the first texture layer image T1. ; It can be represented as a projection transformation matrix from a 3D texture to a 2D image. This can be understood as the pixel coordinates of the first two-dimensional image. The pixel value.

[0064] The technical solution of this disclosure embodiment obtains a layer template corresponding to the first two-dimensional image, the layer template including multiple layers; determines the layer corresponding to each second texture detail information, adds the corresponding second texture detail information to each layer; and obtains a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each processed layer. This achieves independent carrying of multiple texture details through layering, avoiding the problem of multiple texture details overlapping and covering in the same layer, and effectively improving the texture effect and image presentation quality of the two-dimensional image.

[0065] Figure 4 This is a schematic flowchart illustrating another image processing method provided in this embodiment. The technical solution of this embodiment can be combined with other embodiments; for the same or related parts, they can be described in conjunction with the descriptions of other embodiments, and will not be repeated here. Figure 4 As shown, the method in this embodiment may specifically include: S410. Obtain a first two-dimensional image, wherein the first two-dimensional image is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene; the first three-dimensional model includes multiple first local regions.

[0066] S420. Determine the second local region in the first two-dimensional image that corresponds to each of the first local regions.

[0067] S430. Based on the model texture data of the first three-dimensional model in the three-dimensional scene and each of the second local regions, obtain the second texture detail information corresponding to each of the second local regions.

[0068] S440. Obtain a layer template corresponding to the first two-dimensional image, wherein the layer template includes multiple layers.

[0069] S450. Determine the layer corresponding to each of the second texture detail information, and add the corresponding second texture detail information to each of the layers.

[0070] S460. Obtain the position information and first lighting information of the first three-dimensional model in the three-dimensional scene.

[0071] The first lighting information can be understood as the set of all lighting parameters acting on the first 3D model in the 3D scene. The first lighting information may include one of the following: light source position information, light intensity information, light color information, and shadow projection information. The purpose of obtaining the first lighting information is to reproduce the lighting and shadow rendering effect on the model surface, so that the lighting and shadow representation of the second 2D image is aligned with the real-time lighting state of the first 3D model in the 3D scene, avoiding lighting and shadow misalignment and brightness deviation in the 2D image, and thus ensuring that the generated second 2D image visually matches the native rendering effect of the 3D scene.

[0072] S470. Based on the location information and the first illumination information, determine the second illumination information corresponding to each processed layer.

[0073] The second lighting information can be understood as a set of directional lighting parameters generated for each independent layer. Specifically, it is a set of directional lighting parameters generated for each independent layer within the layer template, based on the scene position information and global first lighting information of the first 3D model. Optionally, the second lighting information may include one of the following: local lighting intensity, light and shadow offset, and specular weight of the first local area corresponding to the layer. In this embodiment, the second lighting information can be used to individually adapt the lighting and shadow rendering effect of the texture details within the layer to ensure that the texture lighting and shadow of each layer are aligned with the global lighting of the 3D scene.

[0074] Specifically, based on the position information of the first 3D model in the 3D scene and the first lighting information, independent light source channels are determined according to the lighting attributes of the first local area corresponding to each layer. Within the light source channel, subdivision parameters such as local lighting intensity, light and shadow offset, and highlight weight of the corresponding area of ​​the layer are calculated to generate the second lighting information corresponding to the layer. The light source channels of different layers are isolated from each other, which can avoid interference between lighting parameters. In this embodiment of the disclosure, determining the corresponding independent light source channel based on the position information of the first 3D model in the 3D scene and the first lighting information, according to the lighting attributes of the first local area corresponding to each layer, may include: pre-setting independent light source channels corresponding to different lighting intensity ranges, calculating the lighting weight of the first local area corresponding to each layer, and determining the light source channel corresponding to each layer for the lighting intensity range corresponding to each lighting weight.

[0075] S480. Based on the first two-dimensional image, each processed layer, and the second illumination information corresponding to each processed layer, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

[0076] In one scenario, for each processed layer, the second lighting information corresponding to the processed image is superimposed onto the second texture detail information within that layer to obtain a layer with added lighting information. A second texture layer image is obtained based on each layer with added lighting information. A second two-dimensional image corresponding to the first two-dimensional image is obtained based on the first two-dimensional image and the second texture layer image. That is, the second texture layer image is superimposed on the first two-dimensional image to obtain the second two-dimensional image corresponding to the first two-dimensional image.

[0077] Optionally, the second lighting information corresponding to the processed image is superimposed onto the second texture detail information within this layer using the following formula: ; in, It can represent texture coordinates The pixel values ​​of the texture to be illuminated after the lighting has been blended. T2 can represent the processed layer. The processed layer in texture coordinates The pixel value. This can represent the processed layer in texture coordinates. The second illumination value.

[0078] In this embodiment of the disclosure, before obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the second lighting information corresponding to each processed layer, the method further includes: optimizing the second lighting information corresponding to each processed layer to eliminate lighting inconsistencies between layers, thereby ensuring that the texture lighting effect of the three-dimensional model in the generated second two-dimensional image is more compatible with the rendering effect of the three-dimensional scene. Optionally, the optimization process may include one of the following: lighting boundary smoothing transition processing, lighting accuracy adaptive downsampling processing, lighting outlier correction processing, and lighting parameter normalization alignment processing.

[0079] The technical solution of this disclosure embodiment obtains the position information and first lighting information of the first three-dimensional model in the three-dimensional scene; determines the second lighting information corresponding to each processed layer based on the position information and the first lighting information; and obtains the second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the second lighting information corresponding to each processed layer, thereby avoiding interference from multiple local texture lighting overlaps.

[0080] This disclosure provides an optional embodiment of an image processing method, taking a 3D model as an example of a virtual character model. The surface of this model includes a clothing area, a skin area, and an accessory area. Specific implementation details can be found in the following embodiments. Technical features that are the same as or similar to those in the above embodiments will not be repeated here. The method of this embodiment specifically includes the following steps: Step 1: After obtaining a 2D rendered image of a virtual character model in a 3D scene, the image is synthesized to generate a 2D character image (see...). Figure 5 In the case of [missing information], obtain the model texture map used by the virtual character model in the 3D scene, and the coordinate mapping relationship between the pixels of the model texture map and the vertices of the virtual character model surface. The first local region in the virtual character model includes the clothing model region, the skin model region, and the accessory model region.

[0081] Step 2: Taking the clothing model area of ​​the virtual character model as an example (see...) Figure 6 The process involves obtaining the clothing texture details of the clothing model area in the 3D scene, and assigning the clothing texture details to the corresponding layer so that the layer can carry the clothing texture details.

[0082] Step 3: Based on the position of the virtual character model in the 3D scene and the ambient lighting information, determine the local lighting information corresponding to the layer containing the clothing texture details. Then, overlay this local lighting information onto the clothing texture details corresponding to this layer.

[0083] Step 4: Based on the 2D character image and a layer that carries clothing texture details and overlays local lighting information, generate a clothing texture image (see...). Figure 7 Based on the clothing texture image and the 2D character image, the processed 2D character image is obtained (see...). Figure 8 In this embodiment of the disclosure, the clothing area of ​​the character in the processed two-dimensional character image has clothing texture details.

[0084] In this embodiment of the disclosure, the processed two-dimensional character image can be obtained based on the clothing texture image and the two-dimensional character image according to the following formula: Among them, among them, It can represent the pixel coordinates of the processed 2D character image. The output pixel values ​​generated by the fusion are shown. T3 can represent the clothing texture image. It can represent the pixel coordinates in a clothing texture image. The alpha channel value at that location. It can represent texture coordinates determined by the projection transformation matrix. Pixel values ​​sampled from the clothing texture image T3. This can be understood as the pixel coordinates of a two-dimensional character image. The pixel value.

[0085] Before generating the clothing texture image based on the layer carrying clothing texture details and superimposed local lighting information and the 2D character image, the process also includes: aligning the layer carrying clothing texture details and superimposed local lighting information and the 2D character image.

[0086] The technical solution of this disclosure solves the technical problem that existing image processing relies solely on two-dimensional image pixel processing, which cannot preserve the original texture features of the model and is prone to erasing texture details. It realizes the processing logic of introducing the lossless original texture information of the three-dimensional model into the post-processing process without changing the original two-dimensional image quality optimization link. This achieves the technical effect of improving the texture integrity of the output image and making the image performance highly consistent with the original design expectations of the three-dimensional model. It can directly adapt to the fine image quality requirements of various media content production scenarios such as game rendering and film and television post-production.

[0087] Figure 9 This is a schematic diagram of the structure of an image processing apparatus provided in an embodiment of the present disclosure. The image processing... Figure 9As shown, the image processing device includes: a first module 910, a second module 920, and a third module 930.

[0088] The first module 910 is used to acquire a first two-dimensional image, which is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene. The second module 920 is used to obtain the first texture detail information of the first three-dimensional model in the three-dimensional scene; The third module 930 is used to obtain a second two-dimensional image corresponding to the first two-dimensional image based on the first texture detail information and the first two-dimensional image.

[0089] The technical solution of this disclosure involves obtaining a first two-dimensional image by acquiring a two-dimensional rendered image of a first three-dimensional model in a three-dimensional scene and processing it using a preset two-dimensional image processing method. Lossless original texture details are directly extracted from the three-dimensional scene data of the first three-dimensional model to obtain first texture detail information of the first three-dimensional model in the three-dimensional scene. Based on the first texture detail information, the missing texture details in the first two-dimensional image are supplemented to obtain a second two-dimensional image corresponding to the first two-dimensional image. This technical solution solves the technical problem that existing image processing methods, which rely solely on two-dimensional image pixel processing, cannot preserve the original texture features of the model and are prone to erasing texture details. It achieves the processing logic of introducing lossless original texture information of the three-dimensional model into the post-processing flow without altering the original two-dimensional image quality optimization link. This results in improved texture integrity of the output image and a high degree of consistency between the image performance and the original design expectations of the three-dimensional model, directly adapting to the refined image quality requirements of various media content production scenarios such as game rendering and film post-production.

[0090] In some embodiments of this disclosure, optionally, the first three-dimensional model includes a plurality of first local regions; the second module 920 is used to determine a second local region in the first two-dimensional image corresponding to each of the first local regions; and to obtain second texture detail information corresponding to each of the second local regions based on the model texture data of the first three-dimensional model in the three-dimensional scene and each of the second local regions; and the third module 930 is used to obtain a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each of the second texture detail information.

[0091] In some embodiments of this disclosure, optionally, the third module 930 is configured to obtain a layer template corresponding to the first two-dimensional image, the layer template including multiple layers; determine the layer corresponding to each of the second texture detail information, add the corresponding second texture detail information to each of the layers; and obtain a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each of the processed layers.

[0092] In some embodiments of this disclosure, optionally, the layer is associated with the first local region, and the third module 930 is used to determine the first local region corresponding to the second texture detail information, and to use the layer corresponding to the first local region as the layer corresponding to the second texture detail information.

[0093] In some embodiments of this disclosure, optionally, the third module 930 is configured to acquire the position information and first lighting information of the first three-dimensional model in the three-dimensional scene; determine the second lighting information corresponding to each processed layer based on the position information and the first lighting information; and obtain a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the second lighting information corresponding to each processed layer.

[0094] In some embodiments of this disclosure, the image processing apparatus may optionally further include a fourth module, which is configured to optimize the second illumination information corresponding to each processed layer before obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the second illumination information corresponding to each processed layer.

[0095] In some embodiments of this disclosure, optionally, the third module 930 is used to obtain transparency channel information corresponding to each processed layer; the transparency channel information is used to characterize the transparency channel value of each pixel in the processed layer; and based on the first two-dimensional image, each processed layer and the transparency channel information corresponding to each processed layer, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

[0096] In some embodiments of this disclosure, optionally, the second module 920 is used to obtain the model texture map associated with the three-dimensional scene of the first three-dimensional model, and the coordinate mapping relationship between the pixels of the model texture map and the vertices of the surface of the first three-dimensional model; and to obtain the first texture detail information of the first three-dimensional model based on the coordinate mapping relationship and the model texture map.

[0097] The image processing apparatus provided in this disclosure can execute the image processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0098] It is worth noting that the various units and modules included in the above-mentioned image processing device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the protection scope of the embodiments of this disclosure.

[0099] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0100] like Figure 10 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0101] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0102] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as image processing methods.

[0103] In some embodiments, the image processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of the image processing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the image processing method by any other suitable means (e.g., by means of firmware).

[0104] Various embodiments of the systems and techniques described above can be implemented in digital circuit systems, integrated circuits, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-chips (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, at least one input device, and at least one output device.

[0105] Computer programs for implementing the image processing methods of this disclosure can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0106] This disclosure provides a computer-readable storage medium storing computer instructions for causing a processor to execute an image processing method, comprising: acquiring a first two-dimensional image, wherein the first two-dimensional image is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene; acquiring first texture detail information of the first three-dimensional model in the three-dimensional scene; and obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first texture detail information and the first two-dimensional image.

[0107] In the context of this disclosure, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0108] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0109] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0110] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and Virtual Private Servers (VPS) in terms of management difficulty and weak business scalability.

[0111] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of embodiments of this disclosure.

[0112] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements an image processing method according to any embodiment of this disclosure.

[0113] In implementing a computer program product, computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0114] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0115] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. An image processing method, characterized in that, The method includes: Obtain a first two-dimensional image, which is a two-dimensional rendered image of the first three-dimensional model in a three-dimensional scene obtained through preset two-dimensional image processing; Obtain the first texture detail information of the first three-dimensional model in the three-dimensional scene; Based on the first texture detail information and the first two-dimensional image, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

2. The method according to claim 1, characterized in that the first three-dimensional model includes a plurality of first local regions; the step of obtaining the first texture detail information of the first three-dimensional model in the three-dimensional scene includes: Determine the second local region in the first two-dimensional image that corresponds to each of the first local regions; Based on the model texture data of the first three-dimensional model in the three-dimensional scene and each of the second local regions, second texture detail information corresponding to each of the second local regions is obtained; The step of obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first texture detail information and the first two-dimensional image includes: Based on the first two-dimensional image and each of the second texture detail information, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

3. The method according to claim 2, characterized in that, The step of obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each of the second texture detail information includes: Obtain a layer template corresponding to the first two-dimensional image, wherein the layer template includes multiple layers; Determine the layer corresponding to each of the second texture detail information, and add the corresponding second texture detail information to each of the layers; Based on the first two-dimensional image and each of the processed layers, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

4. The method according to claim 3, characterized in that, The layer is associated with the first local region, and determining the layer corresponding to each of the second texture detail information includes: A first local region corresponding to the second texture detail information is determined, and the layer corresponding to the first local region is taken as the layer corresponding to the second texture detail information.

5. The method according to claim 3, characterized in that, The step of obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each processed layer includes: Obtain the position information and first lighting information of the first 3D model in the 3D scene; Based on the location information and the first illumination information, determine the second illumination information corresponding to each processed layer; Based on the first two-dimensional image, each processed layer, and the second illumination information corresponding to each processed layer, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

6. The method according to claim 5, characterized in that, before obtaining the second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image, each processed layer, and the second illumination information corresponding to each processed layer, the method further includes: The second lighting information corresponding to each processed layer is optimized.

7. The method according to claim 3, characterized in that, The step of obtaining a second two-dimensional image corresponding to the first two-dimensional image based on the first two-dimensional image and each processed layer includes: Obtain the transparency channel information corresponding to each processed layer; the transparency channel information is used to characterize the transparency channel value of each pixel in the processed layer. Based on the first two-dimensional image, each processed layer, and the transparency channel information corresponding to each processed layer, a second two-dimensional image corresponding to the first two-dimensional image is obtained.

8. The method according to claim 1, characterized in that, The step of obtaining the first texture detail information of the first 3D model in the 3D scene includes: Obtain the model texture map associated with the first three-dimensional model in the three-dimensional scene, and the coordinate mapping relationship between the pixels of the model texture map and the vertices of the surface of the first three-dimensional model; Based on the coordinate mapping relationship and the model texture map, the first texture detail information of the first three-dimensional model is obtained.

9. An image processing apparatus, characterized in that, include: The first module is used to acquire a first two-dimensional image, which is obtained by processing a preset two-dimensional image of a first three-dimensional model in a three-dimensional scene. The second module is used to obtain the first texture detail information of the first three-dimensional model in the three-dimensional scene; The third module is used to obtain a second two-dimensional image corresponding to the first two-dimensional image based on the first texture detail information and the first two-dimensional image.

10. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the image processing method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the image processing method according to any one of claims 1-8.

Images