JPEG2000Based On OpenMP Parallel Coding Algorithm And Compressed Sensing Coding Algorithm

People are constantly striving for perfect life experience, at the same time, the requirements on the quality of digital images are higher and higher. It means that more image data is need, and the faster transfer speed of image is expected in the limited bandwidth. Facing these severe challenges, people must improve the existing image coding algorithms to meet the increasingly demands.JPEG2000is in the spotlight among the existing image coding algorithms. The excellent performance of compression, realization of embedded bit encoding and the compression and transmission of progressive data are the key characteristics of JPEG2000. But, the high complexity and the long run-time of encoding and decoding are the disadvantages of JPEG2000. How to improve the speed of system encoding and decoding is become a problem, when the encoding or decoding of batch data is need. As multi-core technology is widely used in personal computers, the better use of existing resources, in particular the use of multi-core programming technology, to realize the rapid encoding and decoding is an effective way to solve the above problems.JPEG2000parallel encoding algorithm based on OpenMP is proposed in this paper. The original JPEG2000algorithm is improved by OpenMP. It makes the algorithm adapt the multi-threaded parallel implementation and get higher coding efficiency. Experimental results show, the parallel encoding algorithm can effectively improve the image coding efficiency and the CPU utilization, with the increase of the threads number. The proposed algorithm can use fully the advantage of multi-core processors and be more suitable to the rapid transmission of the rich image data in limited bandwidth.The innovation of the image encoding algorithm is the pursuit of scientists, so compressed sensing algorithm get high degree of attention from academia as a change theory of sample field. The basic idea is that the data is sampled in low sampling rate, and then the original data can be reconstructed by a little numbers of data, so that it can reduce data storage capacity. When the original data frequency is low, the reconstructed original data can get higher quality by a appropriate reconstruction algorithm. This performance is the same with image compression.The application of compressed sensing in image coding is discussed in this article. Compressed sensing reconstruction algorithm involves highly complex floating-point matrix, so the speed of system decoding is slow. In order to improve the decoding speed, the realization of reconstruction parallel processing algorithm based on OpenMP is researched and then compressed sensing image encoding parallel algorithm based on OpenMP is proposed. Experimental results show, the proposed algorithm can code simply and get a high compression. Moreover, it can effectively reduce the system decoding time and get a better quality of reconstructed image.