Research On Image Compression Technologies Of Operation Based On GPU

With the rapid development of digital technology, the data increased greatly in both static image and dynamic video image. It is noticeable how to decrease the redundant data in order to save or transmit information more efficiently. So far the GPU of NIVIDIA has evolved into the eighth generation, which increasingly dominates the high-powered general purpose computer field. This essay is written to show the way GPU encodes the image.At the beginning, I describe the model of CUDA, which is mainly made up of CPU+GPU. CPU is in charge of the serial work which is highly logical, and as for GPU, the parallel processing which costs more workload in computing.In this paper, a JPEG image compression coding system based on GPU is realized. Based on the analysis of the original JPEG coding algorithm, a concurrent JPEG coding algorithm which is applicable to CUDA platform is proposed. Most important of all, the paper studies the parallel DCT transformation which can be applied based on GPU and analyzes the parallel Huffman coding method. The paper realizes JPEG image compression coding method based on GPU and analyzes the algorithms through several aspects, and indicates the feasibility of GPU concurrent compression.In this paper, the MPEG-2 compressing and coding of video image based on GPU is also realized, and the basic principle of MPEG-2 is analyzed. The paper further researches on the feasibility of the concurrent algorithm and proposes the concurrent algorithm of CPU+GPU and 2-level concurrent algorithm of CUDA. In addition, the key module of MPEG-2 is studied in detail. The paper proposes the concurrent algorithm based on GPU and analyzes the flow of each module, the data distribution of CUDA programming model and the corresponding image processing unit. The paper analyzes the integral performance of concurrent compressing algorithm through compressing ratio, PSNR and coding efficiency, which shows that the proposed method in this paper is significantly efficient and robust. Meanwhile, the paper analyzes the coding speed of several modules in a specific way.