Parallelization of Digital Processing of Colour Images

Digital image processing, especially working with color images, has become an integral part of modern technologies. Color images are usually stored in the RGB (Red, Green, Blue) model, where each pixel consists of three color components. Since each component can be processed independently, parallel computing technologies are widely applied in this field.Parallelization refers to the technique of executing multiple tasks simultaneously, significantly increasing processing speed. In color image processing, each channel (R, G, B), each pixel, or image blocks can be processed by separate processors or threads. This not only saves time but also allows for real-time processing of large-scale images.Parallel processing techniques are effectively used in various fields such as artificial intelligence, medical imaging, video surveillance, and graphic editing applications. With the help of GPUs (graphics processing units) and multi-core CPUs, parallel processing is achieved using technologies like OpenMP, CUDA, OpenCL, and MPI.In addition, tasks like neural network-based analysis, image segmentation, filtering, sharpening, and color balance adjustments are also executed in parallel.