Research On Lossless Compression Of Sequential Images For Space Astronomical Observation

Astronomical observation is of great significance for the study of astronomy,and the integrity of astronomical images is more important to astronomers.The pressure of space storage and transmission can be reduced,and clear and complete astronomical images can be obtained by lossless compression of astronomical images.Sequential astronomical images to be obtained by ASO-S are used as the main research object.This kind of astronomical images are obtained by continuously observing the point object,so they have some common features,such as high time and space redundancy.Aiming at these characteristics of the research object,a sequential astronomical image lossless compression algorithm combining intra-frame and inter-frame was proposed.The algorithm consists of two parts: the intra-frame lossless compression algorithm and the inter-frame lossless compression algorithm.The first frame of each group of images is subjected to intra-frame lossless compression,and the remaining frames are subjected to inter-frame lossless compression.This RICE algorithm and the JPEG-LS algorithm are introduced as the intra-frame compression algorithm.In the RICE algorithm,the maximum value of the pre-processed sample is used to improve the k-value selection algorithm in the original algorithm,which reduces the complexity of the algorithm.By comparing the two algorithms,the test results show that the JPEG-LS algorithm is more suitable for the compression of spatial astronomical images.Therefore,the JPEG-LS algorithm is used as the intra-frame lossless compression algorithm.Generally,the inter-frame lossless compression algorithm only includes two parts of inter-frame prediction and encoder.According to the characteristics of astronomical images,the improved inter-frame lossless compression algorithm is proposed,which consists of inter-frame prediction,error-frame prediction and encoder.The structure is more advantageous for the compression of astronomical images.The time redundancybetween adjacent frames can be reduced by inter-frame prediction.Spatial redundancy can be further reduced by error frame prediction,while coding redundancy can be reduced by encoders.In inter-frame prediction,the inter-frame prediction based on global motion compensation and local motion compensation is mainly introduced.In the error-frame prediction,the fixed predictor of JPEG-LS is mainly used.In the encoder,the Huffman encoder and arithmetic encoder are mainly introduced.The test results show that the compression performance of inter-frame prediction based on global motion compensation is better than that of inter-frame prediction based on local motion compensation,and the coding performance of arithmetic coder is better than that of Huffman coder.Therefore,the inter-frame prediction based on global motion compensation,the error-frame prediction and arithmetic coder are used as the inter-frame lossless compression algorithm.In the test of the coronagraph images,the compression performance of the improved inter-frame lossless compression algorithm is reduced by an average of 1.2 bit/pixel compared to the intra-frame lossless compression algorithm.And in the full-sun images test,the compression performance of the improved inter-frame lossless compression algorithm is reduced by an average of 0.2 bit/pixel compared to the intra-frame lossless compression algorithm.In both test images,the compression time of the improved inter-frame lossless compression algorithm is reduced by more than 96% compared to the intra-frame lossless compression algorithm.