Modern GPUs feature two programmable parallel processing units: the vertex processor and the fragment processor. When utilizing a GPU to execute general-purpose computing tasks such as image processing, the primary task involves mapping the task at hand onto the GPU's supported graphics rendering pipeline.

The conventional approach involves expressing the input data for computational tasks using attributes such as vertex positions, colors, normal vectors, or graphical rendering elements like textures; the corresponding processing algorithms are then decomposed into a series of execution steps and rewritten as GPU vertex processing shaders or fragment processing shaders; next, a 3D API is invoked to execute the graphics rendering operation, and a fragment shader is invoked for further processing; finally, the rendering results stored in the frame buffer constitute the output data of the algorithm.

Although there are numerous digital image processing algorithms and their specific implementation processes vary significantly, when utilizing GPUs for parallel processing, several common key technical challenges must be addressed, such as data loading, feedback of computation results, and their storage.

The following section analyzes these common issues and proposes corresponding solutions.

1. Data Loading

In the GPU's stream-based programming model, all data must be loaded and processed in "stream" format and accessed via an abstract 3D API. When utilizing the GPU for image processing, the most direct and effective method for data loading is to package the images to be processed as textures, loading and processing them during the rendering of quadrilaterals. Additionally, to ensure that the GPU's fragment shader can process the texture image pixel-by-pixel, the projection transformation must be set to an orthogonal projection, and the view frustum defined by the view transformation must match the dimensions of the texture; this ensures that each rasterized fragment corresponds exactly to each texel in the texture. For other parameters used in image processing algorithms, if the data volume is small, they can be configured directly through interface functions; if there are numerous parameters, they should also be packaged as textures and transmitted to the GPU. During this packaging process, full utilization of the four channels (R, G, B, A) inherent to texture images should be ensured.

2. Feedback and saving of calculation results

Applications render textured quadrilaterals by invoking a 3D API, activate fragment shaders on the GPU to perform image processing, and the direct rendering output from the GPU fragment shader is a frame buffer—which corresponds to a window on the computer screen traditionally used to hold the pixels to be displayed; however, in GPU stream computing, this frame buffer can be utilized to store computed results. Although the CPU can directly read from and write to this frame buffer via the 3D API, copying the rendering results from the frame buffer to system memory for storage, the size of the frame buffer is constrained by the window size, and due to the bandwidth limitations of the AGP bus (2.1 GB/s), data transfer from the graphics memory to the system memory is also受限.

The mirror transformation GPU rendering process primarily consists of the following steps:

1. Set up one input texture;

2. Perform texture sampling on the input texture;

3. Set the transformation matrix;

4. In the vertex shader, the input vertices are multiplied by the transformation matrix;

5. Output image data;