Mobile terminal volume cloud rendering method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a mobile terminal volume cloud rendering method and device, electronic equipment, a storage medium and a program product. The method comprises the steps that a rendering texture area with the resolution lower than that of a mobile terminal screen is created; rendering the cloud volume data of the current frame under the visual angle of the virtual camera to a rendering texture area; in the rendering process, executing a rendering strategy corresponding to each pixel to determine a cloud body rendering parameter of each pixel in the rendering texture region, and obtaining a low-resolution volume cloud image corresponding to the current frame after rendering is completed; and reconstructing a high-resolution volume cloud image corresponding to the current frame according to the low-resolution volume cloud image and the high-resolution volume cloud image of the previous frame. According to the invention, the computing load and power consumption of the mobile terminal can be obviously reduced on the premise of ensuring the volume cloud rendering quality.

Description

Technical Field

[0001] This invention relates to the field of image rendering technology, and more specifically, to a mobile volumetric cloud rendering method, apparatus, electronic device, storage medium, and program product. Background Technology

[0002] With the continuous improvement of mobile device graphics processing capabilities, users are demanding higher levels of visual realism in mobile 3D graphics applications (such as games, virtual reality, and augmented reality). Volumetric clouds refer to the use of graphics engines to simulate the semi-transparent, irregular appearance of real clouds and fog. Due to their realistic sense of volume and natural shape changes, they are of great significance in constructing virtual environments.

[0003] On high-performance computing platforms (such as personal computers or game consoles), volumetric clouds are typically implemented using a ray-marching-based rendering method. This method densely samples the 3D cloud density field along the view direction in the pixel shader, thereby generating highly realistic cloud visual effects. However, such algorithms have extremely high computational complexity and rely on powerful GPU computing power, making them difficult to apply directly on resource-constrained mobile devices.

[0004] Currently, volumetric cloud rendering for mobile devices mainly falls into the following categories: The first is the planar fragment (Billboard) technique. This method has extremely low performance overhead, but lacks realistic depth information and volume perception, making it difficult to meet the visual requirements of high-quality application scenarios. The second is a simplified modeling of volumetric lighting effects. While this method provides some volume perception, it cannot reproduce complex cloud structures and realistic atmospheric optical phenomena. The third attempts to directly port mature PC-based ray stepping schemes to mobile devices. However, due to the lack of targeted algorithm optimization, this results in a significant drop in rendering frame rate, excessive GPU load, and a sharp increase in power consumption, severely impacting device battery life and system stability.

[0005] In summary, existing mobile cloud rendering technologies suffer from the trade-off between visual quality and operational efficiency. Therefore, there is an urgent need for a novel volumetric cloud rendering method that can significantly reduce computational load and power consumption while maintaining visual quality. Summary of the Invention

[0006] In view of this, the purpose of this invention is to provide a mobile volumetric cloud rendering method, apparatus, electronic device, storage medium, and program product that can significantly reduce the computational load and power consumption of mobile devices while ensuring the quality of volumetric cloud rendering. To achieve the above objective, the technical solutions adopted in the embodiments of this invention are as follows: In a first aspect, the present invention provides a mobile device volumetric cloud rendering method, the method comprising: creating a rendering texture area with a resolution lower than that of the mobile device screen; rendering cloud data from the virtual camera perspective of the current frame to the rendering texture area; during the rendering process, executing a rendering strategy corresponding to each pixel to determine the cloud rendering parameters of each pixel in the rendering texture area; obtaining a low-resolution volumetric cloud image corresponding to the current frame after rendering is completed; and reconstructing a high-resolution volumetric cloud image corresponding to the current frame based on the low-resolution volumetric cloud image and the high-resolution volumetric cloud image of the previous frame.

[0007] In an optional implementation, during the rendering process, the rendering strategy corresponding to each pixel is executed to determine the cloud rendering parameters of each pixel in the rendering texture area. After rendering is completed, a low-resolution volumetric cloud image corresponding to the current frame is obtained, including: for pixels whose world coordinate change is less than a preset threshold, the cloud rendering parameter estimate and the cloud rendering parameters corresponding to the pixel at the same position in the previous frame are weighted and fused to obtain the final cloud rendering parameters of the pixel; for pixels whose world coordinate change is greater than or equal to the preset threshold, multiple ray stepping strategies are executed to determine the final cloud rendering parameters of the pixel.

[0008] In an optional implementation, for pixels whose world coordinate changes are greater than or equal to a preset threshold, a multiple ray stepping strategy is executed to determine the final cloud rendering parameters of the pixel, including: determining the sampling frequency and the number of steps based on the spatial feature importance of the region where the pixel is located; and using the sampling frequency and the number of steps to execute the multiple ray stepping strategy to determine the final cloud rendering parameters of the pixel.

[0009] In an optional implementation, the method further includes: during the execution of the ray stepping strategy, for each sampling point, calculating the cosine value of the angle between the viewing direction and the light source direction, and mapping the cosine value of the angle and the cloud density value of the sampling point to texture coordinates; obtaining the scattered color intensity corresponding to the texture coordinates from a pre-generated two-dimensional lookup table, which is used to participate in the cumulative calculation of cloud rendering parameters; wherein, the two-dimensional lookup table is used to maintain the scattered color intensity corresponding to each texture coordinate.

[0010] In an optional implementation, reconstructing the high-resolution volumetric cloud image corresponding to the current frame based on the low-resolution volumetric cloud image and the high-resolution volumetric cloud image of the previous frame includes: obtaining motion vector information corresponding to each pixel in the current frame; wherein the motion vector information represents the screen space displacement of the pixel between adjacent frames; aligning the high-resolution volumetric cloud image with the virtual camera viewpoint of the current frame using the pixel motion vector information; upsampling the low-resolution volumetric cloud image and then performing weighted fusion with the aligned high-resolution volumetric cloud image to obtain the high-resolution volumetric cloud image corresponding to the current frame.

[0011] In an optional implementation, the method further includes: storing the high-resolution volumetric cloud image corresponding to the current frame into a buffer for reconstructing the high-resolution volumetric cloud image of the next frame.

[0012] Secondly, the present invention provides a mobile volumetric cloud rendering device, comprising: a creation module, a rendering module, and a reconstruction module; the creation module is used to create a rendering texture area with a resolution lower than that of the mobile screen; the rendering module is used to render cloud data from the virtual camera perspective of the current frame to the rendering texture area; during the rendering process, the rendering strategy corresponding to each pixel is executed to determine the cloud rendering parameters of each pixel in the rendering texture area, and after rendering is completed, a low-resolution volumetric cloud image corresponding to the current frame is obtained; the reconstruction module is used to reconstruct a high-resolution volumetric cloud image corresponding to the current frame based on the low-resolution volumetric cloud image and the high-resolution volumetric cloud image of the previous frame.

[0013] Thirdly, the present invention provides an electronic device including a processor and a memory, wherein the memory stores machine-executable instructions that can be executed by the processor, and the processor can execute the machine-executable instructions to implement the mobile volumetric cloud rendering method described in any of the foregoing embodiments.

[0014] Fourthly, the present invention provides a storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the mobile volumetric cloud rendering method as described in the first aspect above.

[0015] Fifthly, the present invention provides a program product on which a computer program runs, and the computer program, when run, implements the mobile terminal volumetric cloud rendering method as described in the first aspect above.

[0016] The mobile volumetric cloud rendering method, apparatus, electronic device, storage medium, and program product provided in this invention first create a rendering texture area with a resolution lower than the native resolution of the mobile screen. This reduces the total number of pixels that need to be processed, thereby directly alleviating the computational pressure and power consumption of the mobile device. Next, during the rendering process, an adaptive rendering strategy is dynamically executed for each pixel to ensure that key visual details and spatial hierarchy are preserved even at low resolution, generating a high-quality low-resolution volumetric cloud image. Subsequently, the low-resolution result of this frame is used to perform cross-resolution spatiotemporal reconstruction with the existing high-resolution volumetric cloud image of the previous frame, ultimately restoring the current frame cloud image with high-resolution rendering quality. The entire process can significantly reduce the amount of shading computation and video memory bandwidth consumption, thereby achieving the goal of efficiently running high-quality volumetric cloud rendering on mobile devices.

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This diagram illustrates the application environment of the mobile volumetric cloud rendering method provided in an embodiment of the present invention. Figure 2 A schematic flowchart of the mobile volumetric cloud rendering method provided in an embodiment of the present invention is shown; Figure 3 This diagram illustrates the functional modules of the mobile volumetric cloud rendering device provided in an embodiment of the present invention. Figure 4 A structural block diagram of an electronic device provided in an embodiment of the present invention is shown. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0021] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0022] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0023] First, the terms used in the embodiments of this invention will be introduced and explained: Ray stepping is a rendering method in computer graphics where rays are iteratively traversed, effectively dividing each ray into smaller segments and sampling certain functions at each step. This method can be applied to scenarios such as volumetric rendering.

[0024] The technical solutions and their effects according to the embodiments of the present invention will be described below through the description of some exemplary implementations. It should be noted that the following implementations can be referred to, learned from, or combined with each other, and the same terms, similar features, and similar implementation steps in different implementations will not be described again.

[0025] Please see Figure 1 , Figure 1 The figure shows a schematic diagram of the application environment of the mobile volumetric cloud rendering method provided in the embodiment of the present invention. As shown in the figure, the application environment includes a mobile terminal 101 and a server 102, wherein the mobile terminal 101 and the server 102 are connected through a communication network 103.

[0026] Mobile device 101 contains applications based on a virtual environment. Users can use these applications on mobile device 101, such as controlling a virtual character to move within the virtual environment. The virtual environment also includes virtual objects such as virtual clouds.

[0027] In some embodiments, the mobile terminal 101 renders a virtual cloud based on data interaction with the server 102, that is, it executes the mobile terminal volumetric cloud rendering method provided in the embodiments of the present invention to solve the technical problems in the prior art.

[0028] In this embodiment of the invention, server 102 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0029] Optionally, the mobile terminal 101 may be, but is not limited to, a smartphone, tablet, laptop, etc., and the server 102 may be, but is not limited to, a game server, live streaming server, etc. The mobile terminal 101 and the server 102 may be directly or indirectly connected via wired or wireless communication, and this embodiment of the invention does not impose any limitations.

[0030] Please see Figure 2 , Figure 2 The diagram illustrates a schematic flowchart of a mobile volumetric cloud rendering method provided in an embodiment of the present invention. The execution subject of this method can be an electronic device, such as... Figure 1 The mobile version 101 is used as an example below to introduce... Figure 2 Steps S201 to S204 are explained as follows: S201: Create a rendering texture area with a resolution lower than that of the mobile screen; S202: Render the cloud data from the virtual camera's perspective in the current frame to the rendering texture area; S203: During the rendering process, the rendering strategy corresponding to each pixel is executed to determine the cloud rendering parameters of each pixel in the rendering texture area. After the rendering is completed, the low-resolution volumetric cloud image corresponding to the current frame is obtained. S204: Reconstruct the high-resolution volumetric cloud image corresponding to the current frame based on the low-resolution volumetric cloud image and the high-resolution volumetric cloud image of the previous frame.

[0031] In the mobile volumetric cloud rendering method provided in this invention, a rendering texture area with a resolution lower than the native resolution of the mobile screen is first created. This reduces the total number of pixels that need to be processed, thereby directly alleviating the computational pressure and power consumption of the mobile device. Then, during the rendering process, an adaptive rendering strategy is dynamically executed for each pixel to ensure that key visual details and spatial hierarchy are preserved even at low resolution, generating a high-quality low-resolution volumetric cloud image. Subsequently, the low-resolution result of this frame is used to perform cross-resolution spatiotemporal reconstruction with the existing high-resolution volumetric cloud image of the previous frame, and finally, the current frame cloud image with high-resolution rendering quality is restored. The entire process can significantly reduce the amount of shading computation and video memory bandwidth consumption, thereby achieving the goal of efficiently running high-quality volumetric cloud rendering on mobile devices.

[0032] Next, the embodiments of the present invention will describe the above. Figure 1 The mobile volumetric cloud rendering process is explained in detail.

[0033] In step S201, the mobile screen resolution refers to the screen resolution of the mobile device, such as 2340×1080 (approximately 2.5 million pixels). Rendering volumetric clouds at this full resolution would consume significant GPU computing resources. Therefore, this embodiment of the invention first creates a low-resolution buffer (e.g., 1 / 4 or 1 / 8 of the screen resolution), which is essentially a separate image storage area much smaller than the actual display screen. For example, if the screen resolution is 1920×1080 (approximately 2 million pixels), the rendering texture area is set to 480×270 (i.e., 1 / 4 resolution, only about 130,000 pixels). This means that the complex ray stepping calculations that originally required processing 2 million pixels now only require processing about 130,000 pixels, reducing the computational load by approximately 93%. This method can directly and significantly reduce the number of pixels that need to be processed, fundamentally alleviating the GPU burden and is key to achieving low power consumption.

[0034] In this embodiment of the invention, after the mobile terminal creates a low-resolution texture area in advance, the GPU output target is set to this texture instead of the main screen before the cloud starts to be rendered in the current frame. Subsequently, the cloud body can be drawn using the ray stepping strategy optimized in this embodiment of the invention, and the low-resolution cloud body rendering parameters, including cloud body color, brightness information, transparency, etc., can be stored for subsequent reconstruction of high-resolution volumetric cloud images.

[0035] In step S202, the embodiment of the present invention first renders the cloud data from the virtual camera viewpoint of the current frame to the rendering texture area.

[0036] The current frame refers to the frame being rendered, a point in time within the real-time execution of a game or application. The virtual camera perspective refers to the "camera" used to observe the world in the virtual environment, determining the position, direction, and angle from which the scene content is viewed. For example, when a virtual camera simulates shooting a virtual model from a particular perspective, it can simulate the view seen from the user's perspective. When the virtual camera's shooting perspective changes, the image of the model captured by the virtual camera also changes accordingly, thus simulating the phenomenon of the user seeing different images of the virtual model from different perspectives. Cloud data describes a data structure that describes information such as cloud density, morphology, and lighting attributes in the virtual environment.

[0037] Through step S202 above, the mobile device can perform subsequent ray-stepping rendering processing on the 3D volumetric cloud model based on the viewpoint position and viewing direction of the virtual camera in the current frame, and write the obtained cloud color and brightness information into the rendering texture area created in step S201. Specifically, in step S203, the mobile device can call the cloud rendering shader to complete the rendering, as shown in steps a1 to a2, as explained below: Step a1: For pixels whose world coordinate change is less than a preset threshold, the cloud rendering parameter estimate and the cloud rendering parameter corresponding to the pixel at the same position in the previous frame are weighted and fused to obtain the final cloud rendering parameter of the pixel. Step a2: For pixels whose world coordinate changes are greater than or equal to a preset threshold, execute multiple ray stepping strategies to determine the final cloud rendering parameters of the pixels.

[0038] In this embodiment of the invention, for each pixel, the corresponding viewing direction can be deduced from its screen coordinates in the current frame, and the world space coordinates corresponding to the pixel can be calculated by combining depth information or volume space mapping relationship; then, the world coordinates are compared with the historical world coordinates stored at the same screen position in the previous frame, and the Euclidean distance or displacement difference between the two is calculated to obtain the change in its world coordinates. The preset threshold can be flexibly set by game engineers based on practical experience, and is not limited here.

[0039] In the first scenario, if the change in world coordinates of a pixel is less than a preset threshold, it indicates that the scene region corresponding to that pixel remains relatively stable between adjacent frames, the virtual camera's perspective remains static or moves slowly, and the cloud appearance exhibits high temporal consistency. In this case, the rendering result of the previous frame can be considered valid. Therefore, there is no need to perform a complex ray tracing process; simply weighting and mixing the historical cloud rendering parameters (such as color, lighting, and transparency) with the current rough estimate yields the final cloud rendering parameters for each pixel.

[0040] Understandably, for pixels in the first scenario described above, there's no need for ray stepping, which reduces computation and improves rendering efficiency. Simultaneously, the reuse of historical cloud rendering parameters incorporates current rough estimates, effectively compensating for visual deviations caused by slight virtual camera shake, slow lighting changes, or the slow drift of the clouds themselves. This avoids "ghosting" or "image retention" resulting from pure reuse, thus further improving rendering quality while maintaining efficiency.

[0041] In the second scenario, if the change in world coordinates of a pixel is greater than or equal to a preset threshold, it indicates that the virtual camera is moving too fast or the viewpoint has changed significantly, disrupting the spatiotemporal consistency between the current frame and the previous frame. In this case, historical rendering results are no longer reliable and cannot be directly reused; therefore, a ray stepping strategy is required to ensure rendering accuracy.

[0042] For pixels in the second case, in order to minimize computational overhead while ensuring visual quality in key areas during the execution of the ray stepping strategy, this embodiment of the invention proposes a spatially adaptive sampling strategy to optimize the ray stepping process. Specifically, step a2 can be implemented as follows: Step 1: Determine the sampling frequency and number of steps based on the spatial importance of the region where the pixel is located; In this embodiment of the invention, the sampling frequency refers to the density of sampling volume cloud data along the line of sight, that is, the number of sampling points per unit distance. The higher the sampling frequency, the smaller the step size of each step, which can capture cloud structure and illumination changes more precisely. The number of steps refers to the maximum or actual number of samplings performed in the entire light path. The more steps, the more accurate the calculation, but the higher the cost.

[0043] For example, for cloud edges, areas with strong light interaction (such as "glare zones" under sunlight), near-field areas, or areas with large noise gradients, a higher sampling frequency and more steps should be used because they are visually salient and rich in detail. On the other hand, for areas with homogeneous density inside the cloud, distant parts far from the viewpoint, or occluded areas that are not visually sensitive, the sampling frequency and number of steps can be appropriately reduced to significantly reduce the computational burden without affecting the overall visual experience.

[0044] To determine the spatial feature importance of each pixel and the required sampling frequency and number of steps, this embodiment of the invention can pre-generate a spatial feature importance map. The value of each pixel in this map reflects the level of attention required for its region during rendering; a higher value indicates a more important region. This importance map can be generated offline through pre-computation or dynamically at runtime. Subsequently, the mobile device can classify different regions according to this importance map and map them to corresponding sampling frequency and number of steps configurations.

[0045] Step 2: Execute multiple ray stepping strategies using sampling frequency and step count to determine the final cloud rendering parameters for each pixel.

[0046] As can be seen, the embodiments of the present invention do not apply a uniform sampling frequency and number of steps to all pixels, but rather implement differentiated processing based on the importance of their respective regions, thereby achieving intelligent allocation of computing resources. This spatial adaptive strategy effectively avoids the problems of performance waste caused by global high sampling or image quality degradation caused by global low sampling in traditional methods, balancing rendering quality and efficiency on mobile devices under the limited computing power.

[0047] In one embodiment of the invention, the number of ray steps can also be optimized, for example, by performing a maximum of 20 ray steps, compared to the 64–128 steps required on traditional PCs. This significantly reduces the computational load on the fragment shader and the time overhead required for the GPU to process volumetric clouds per frame, thereby effectively improving rendering efficiency and reducing power consumption. Although the number of samples is reduced, due to the combined optimization mechanisms of low-resolution rendering, temporal multiplexing, and spatial adaptive sampling, this optimization can still achieve an efficient balance between rendering quality and performance under the limited hardware resources of mobile devices. In one embodiment of the present invention, considering that in the volumetric rendering process, to accurately calculate the brightness of a certain point, it is necessary to integrate the multiple scattering contributions along the entire view path. This integration process involves multiple variables, including the viewpoint direction, the light source direction, and cloud density. If it is calculated in real time for each pixel in every frame, it will result in an extremely high GPU computing load, which is difficult to meet the performance and power consumption requirements of mobile devices.

[0048] To achieve near-realistic cloud lighting effects on mobile devices while avoiding high real-time computation costs, this invention proposes an alternative solution based on a two-dimensional lookup table for determining cloud rendering parameters in the second scenario. Specifically, the complex scattering integral, which would normally require dynamic solution at runtime, is pre-calculated offline or during system initialization and stored as a two-dimensional texture map based on key parameter combinations. This two-dimensional texture map serves as a lookup table, with its horizontal axis (X-axis) representing the cosine of the angle between the viewing direction and the light source direction, and its vertical axis (Y-axis) representing the cloud density value (or normalized density intensity) at the corresponding sampling point. Each texture in the lookup table stores the scattered color intensity value calculated through approximate integration under the condition of "cosine of the angle - cloud density value".

[0049] Therefore, during the execution of the light stepping strategy, the cloud color of each sampling point can be determined as follows, specifically including steps b1 to b2: Step b1: Calculate the cosine of the angle between the viewing direction and the light source direction, and map the cosine of the angle and the cloud density value of the sampling point into texture coordinates; Step b2: Obtain the scattering color intensity corresponding to the texture coordinates from the pre-generated two-dimensional lookup table, which is used to participate in the cumulative calculation of cloud rendering parameters; wherein, the two-dimensional lookup table is used to maintain the scattering color intensity corresponding to each texture coordinate.

[0050] Through the above implementation method, mobile devices do not need to perform complex physical integration calculations in real time during the rendering process. They can obtain physically reasonable lighting responses simply through lightweight texture queries. This not only significantly reduces the computational overhead of shaders and effectively reduces GPU load and overall power consumption, but also solves the technical challenge that mobile devices cannot withstand high-precision scattering integration calculations, achieving an efficient balance between realism and real-time performance.

[0051] After rendering is completed through step S203, the low-resolution volumetric cloud image corresponding to the current frame is obtained. Next, super-resolution reconstruction is performed through step S204 to obtain the high-resolution volumetric cloud image corresponding to the current frame.

[0052] In step S204, this embodiment of the invention first acquires a high-resolution volumetric cloud image from the previous frame. This image is stored in a dedicated history buffer and used as input data for image reconstruction. Then, using the high-resolution output from the previous frame and combining it with the information from the current frame, a high-quality cloud image at the final screen resolution is reconstructed. The reconstruction process is illustrated in steps c1 to c3, as explained below: Step c1: Obtain the motion vector information corresponding to each pixel in the current frame; In this embodiment of the invention, the motion vector represents the screen space displacement of a pixel between adjacent frames. The mobile device can obtain the pixel's position change in world space by calculating the current pixel's position change and mapping it to the screen coordinate system. Specifically, the mobile device can record the world coordinates, normals, and depth information of the geometric surface to which each pixel belongs. By combining the camera view-projection matrix of the current frame and the previous frame, the screen position of the point in the previous frame can be predicted in reverse. The difference between the two is the two-dimensional motion vector of the pixel.

[0053] Step c2: Align the high-resolution volumetric cloud image with the virtual camera viewpoint of the current frame using pixel motion vector information; In this embodiment of the invention, considering that the high-resolution volumetric cloud image of the previous frame was generated in a previous time sequence state, and its pixel layout is based on the virtual camera pose and scene configuration at that time, if it is directly used for fusion in the current frame, it will cause ghosting or misalignment due to camera movement or cloud drift. Therefore, before performing super-resolution reconstruction, a reprojection operation can be performed on the high-resolution cloud image of the previous frame based on motion vectors, that is, mapping each pixel from its original screen position back to the corresponding position under the virtual camera view of the current frame, thereby achieving accurate spatiotemporal alignment of historical data.

[0054] Step c3: Upsample the low-resolution volumetric cloud image and then perform weighted fusion with the aligned high-resolution volumetric cloud image to obtain the high-resolution volumetric cloud image corresponding to the current frame.

[0055] In this embodiment of the invention, upsampling a low-resolution volumetric cloud image refers to the process of enlarging it from its original rendering resolution (such as 1 / 4 screen resolution) to the target display resolution. This can be achieved, but is not limited to, using bilinear interpolation, edge-aware filtering, or other methods. The upsampled image retains the latest detailed features of the current frame, but may have slight blurring or high-frequency loss. Subsequently, the mobile device performs a weighted fusion of the upsampled result with a historical high-resolution image that has undergone reprojection correction to obtain a high-resolution volumetric cloud image.

[0056] Optionally, in the above weighted fusion process, the fusion weights can be dynamically set by relevant technical personnel, and this is not limited here. In practice, steps c1 to c3 can be performed using a full-screen post-processing shader. Specifically, the shader first reads and parses the motion vector texture, performs reprojection correction on the high-resolution volumetric cloud image reconstructed from the previous frame, then upsamples the low-resolution volumetric cloud image of the current frame, and finally weights and blends the two in screen space to output a final screen-resolution, anti-aliased, time-stabilized volumetric cloud image.

[0057] Through the implementation of step S204 above, the embodiments of the present invention can not only eliminate the jagged edges and pixelation caused by low-resolution rendering, but also utilize temporal consistency to smoothly accumulate results from multiple frames, effectively suppressing inter-frame flicker and noise jitter, and improving visual stability. Furthermore, in one embodiment of the present invention, the reconstructed high-resolution volumetric cloud image of the current frame can be saved to a dedicated buffer as historical reference information for the next frame.

[0058] In summary, the mobile volumetric cloud rendering method provided by this invention has the following advantages: First, by rendering the volumetric cloud to a rendering texture area far below the screen resolution (e.g., 1 / 4 or 1 / 8) before super-resolution reconstruction, the GPU computational load is significantly reduced, and the number of shader executions is drastically decreased, which is a prerequisite and key to achieving an overall low-power strategy. Second, in the rendering process, this invention directly reuses historical data for pixels with minor changes, skipping ray stepping and avoiding redundant calculations. For pixels with significant changes, the sampling frequency and number of steps are adaptively adjusted based on the importance of the region, balancing rendering quality and efficiency. Furthermore, in implementing the ray stepping strategy, this invention uses a pre-generated two-dimensional lookup table to replace complex multiple scattering integral calculations, greatly reducing the complexity of lighting calculations. Finally, in resolution reconstruction, this invention can combine motion vectors to reproject and correct historical high-resolution volumetric clouds, then perform image fusion to reconstruct a full-resolution image, ultimately outputting a clear, anti-aliased high-resolution volumetric cloud image. The entire process can balance rendering effects, real-time performance, and low power consumption requirements with limited resources on mobile devices.

[0059] To perform the corresponding steps in the above embodiments and various possible methods, an implementation of the mobile volumetric cloud rendering device 30 is given below. Please refer to [link to relevant documentation]. Figure 3 , Figure 3 A functional block diagram of a mobile volumetric cloud rendering device provided in an embodiment of the present invention is shown. The mobile volumetric cloud rendering device 30 includes: a creation module 301, a rendering module 302, and a reconstruction module 303.

[0060] Create module 301 to create rendering texture areas with a resolution lower than that of mobile screens; The rendering module 302 is used to render cloud data from the virtual camera view of the current frame to the rendering texture area. During the rendering process, the rendering strategy corresponding to each pixel is executed to determine the cloud rendering parameters of each pixel in the rendering texture area. After the rendering is completed, a low-resolution volumetric cloud image corresponding to the current frame is obtained. The reconstruction module 303 is used to reconstruct the high-resolution volumetric cloud image corresponding to the current frame based on the low-resolution volumetric cloud image and the high-resolution volumetric cloud image of the previous frame.

[0061] It is understandable that the creation module 301, rendering module 302, and reconstruction module 303 can be executed collaboratively. Figure 2 Each step in the process is used to achieve the corresponding technical effect.

[0062] It should be noted that the mobile volumetric cloud rendering device 30 provided in this embodiment of the invention can be specific hardware on the device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in this embodiment of the invention are the same as those in the foregoing method embodiments. For the sake of brevity, any parts not mentioned in the device embodiments can be referred to the corresponding content in the foregoing method embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can all be referred to the corresponding processes in the above method embodiments, and will not be repeated here.

[0063] Optionally, the above modules can be stored in the form of software or firmware. Figure 4 The memory shown is in the operating system (OS) of the electronic device 40, and can be... Figure 4 The processor executes the commands. Meanwhile, the data and program code required to execute these modules can be stored in memory.

[0064] Please see Figure 4 , Figure 4 The diagram shows a structural block diagram of an electronic device provided in an embodiment of the present invention. The electronic device 40 may be... Figure 1 The mobile terminal 101 includes a memory 401, a processor 402, and a communication interface 403. The memory 401, processor 402, and communication interface 403 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0065] Optionally, the bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0066] In this embodiment of the invention, the processor 402 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in this embodiment of the invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in this embodiment of the invention can be directly manifested as execution by the hardware processor, or execution by a combination of hardware and software modules within the processor. The software modules may reside in the memory 401, and the processor 402 reads the program instructions from the memory 401 and, in conjunction with its hardware, completes the steps of the aforementioned methods.

[0067] In this embodiment of the invention, the memory 401 can be a non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), or it can be volatile memory, such as RAM. The memory can also be any other medium capable of carrying or storing desired executable program code having an instruction or data structure form and accessible by a computer, but is not limited thereto. The memory in this embodiment of the invention can also be a circuit or any other device capable of implementing a storage function for storing instructions and / or data.

[0068] The memory 401 can be used to store software programs and modules, such as the instructions / modules of the mobile volumetric cloud rendering device 30 provided in this embodiment of the invention. These can be stored in the memory 401 in the form of software or firmware, or embedded in the operating system (OS) of the electronic device 40. The processor 402 executes various functional applications and data processing by executing the software programs and modules stored in the memory 401. The communication interface 403 can be used to communicate with other node devices for signaling or data.

[0069] Understandable. Figure 4 The structure shown is for illustrative purposes only; the electronic device 4 may also include components that are more advanced than those shown. Figure 4 The more or fewer components shown, or having the same Figure 4 The different configurations shown. Figure 4 The components shown can be implemented using hardware, software, or a combination thereof.

[0070] Based on the above embodiments, the present invention also provides a storage medium storing a computer program. When the computer program is executed by a computer, it causes the computer to execute the mobile volumetric cloud rendering method provided in the above embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0071] The present invention can also provide a computer program product for executing a mobile volumetric cloud rendering method, including a computer storage medium storing program code. The instructions included in the program code can be used to execute the methods in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0072] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0073] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs.

[0074] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0075] It should be noted that if the function is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, electronic device, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A mobile volume cloud rendering method, characterized in that, The method comprises: creating a rendering texture area with a resolution lower than the screen resolution of a mobile terminal; rendering cloud data under the virtual camera perspective of the current frame to the rendering texture area; during the rendering process, performing a rendering strategy corresponding to each pixel to determine the cloud rendering parameters of each pixel in the rendering texture area, and obtaining a low-resolution volumetric cloud image corresponding to the current frame after the rendering is completed; reconstructing a high-resolution volumetric cloud image corresponding to the current frame according to the low-resolution volumetric cloud image and a high-resolution volumetric cloud image of a previous frame.

2. The mobile volume cloud rendering method of claim 1, wherein, During the rendering process, performing a rendering strategy corresponding to each pixel to determine the cloud rendering parameters of each pixel in the rendering texture area, and obtaining a low-resolution volumetric cloud image corresponding to the current frame after the rendering is completed, comprises: for a pixel with a world coordinate change amount less than a preset threshold, performing weighted fusion of the cloud rendering parameter estimation value and the cloud rendering parameters corresponding to a pixel at the same position in the previous frame to obtain the final cloud rendering parameters of the pixel; for a pixel with a world coordinate change amount greater than or equal to the preset threshold, performing a multiple-ray stepping strategy to determine the final cloud rendering parameters of the pixel.

3. The mobile volume cloud rendering method of claim 2, wherein, For a pixel with a world coordinate change amount greater than or equal to a preset threshold, performing a multiple-ray stepping strategy to determine the final cloud rendering parameters of the pixel, comprises: determining a sampling frequency and a stepping number according to the spatial feature importance of the region where the pixel is located; performing the multiple-ray stepping strategy using the sampling frequency and the stepping number to determine the final cloud rendering parameters of the pixel.

4. The mobile volume cloud rendering method of claim 2 or 3, wherein, The method further comprises: during the execution of the ray stepping strategy, for each sampling point, calculating a cosine value of the included angle according to the line-of-sight direction and the light source direction, and mapping the cosine value of the included angle and the cloud density value of the sampling point into a texture coordinate; obtaining the scattering color intensity corresponding to the texture coordinate from a pre-generated two-dimensional lookup table, which is used to participate in the cumulative calculation of the cloud rendering parameters; wherein the two-dimensional lookup table is used to maintain the scattering color intensity corresponding to each texture coordinate.

5. The mobile volume cloud rendering method of claim 1, wherein, Reconstructing a high-resolution volumetric cloud image corresponding to the current frame according to the low-resolution volumetric cloud image and a high-resolution volumetric cloud image of a previous frame, comprises: obtaining motion vector information corresponding to each pixel in the current frame; wherein the motion vector information represents the screen space displacement of the pixel between adjacent frames; aligning the high-resolution volumetric cloud image with the virtual camera perspective of the current frame using the pixel motion vector information; after upsampling the low-resolution volumetric cloud image, performing weighted fusion of the upsampled low-resolution volumetric cloud image and the aligned high-resolution volumetric cloud image to obtain the high-resolution volumetric cloud image corresponding to the current frame.

6. The mobile volume cloud rendering method of claim 1, wherein, The method further comprises: storing the high-resolution volumetric cloud image corresponding to the current frame into a buffer area for reconstructing a high-resolution volumetric cloud image of a next frame.

7. A mobile volume cloud rendering apparatus, comprising: comprises: a creating module, a rendering module and a reconstructing module; the creating module is configured to create a rendering texture area with a resolution lower than the screen resolution of a mobile terminal; the rendering module is configured to render cloud data under the virtual camera perspective of the current frame to the rendering texture area; During the rendering process, a rendering strategy corresponding to each pixel is executed to determine cloud body rendering parameters of each pixel in the rendering texture area, and a low-resolution volume cloud image corresponding to the current frame is obtained after the rendering is completed; The reconstruction module is configured to reconstruct a high-resolution volume cloud image corresponding to the current frame according to the low-resolution volume cloud image and a high-resolution volume cloud image of a previous frame.

8. An electronic device, comprising: The mobile terminal comprises a processor and a memory, the memory stores machine executable instructions which can be executed by the processor, and the processor can execute the machine executable instructions to implement the mobile terminal volume cloud rendering method in any one of claims 1-6.

9. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to implement the mobile terminal volume cloud rendering method in any one of claims 1-6.

10. A program product, characterized by The program product runs a computer program, and the computer program is run to implement the mobile terminal volume cloud rendering method in any one of claims 1-6.

Images