The Implementation and Optimization of High-Performance Image Processing Algorithms Based on Artificial Intelligence

Image processing (IP) technology has emerged on the basis of AI, digital imaging technology, and multimedia technology, and people began to use computers to process images to improve image quality and improve human vision. With the advancement of computer vision and AI technology, people want to achieve high performance IP. In the field of IP, techniques such as image segmentation, image compression, and image restoration are active research topics in computer vision. In this paper, we propose IP algorithms such as Artificial Bee Colony(ABC) Optimization Algorithm and Searcher Optimization Algorithm (SOA) for this block of image compression, analyze the image compression effect of these two algorithms, and compare the image compression quality by comparing the PSNR of each algorithm, and the results get that the image compression effect based on artificial bee colony(ABC) Algorithm is better and the image compression code book quality is better with the same compression ratio.