Deep Space Communication Image Compression Algorithms Based On Discrete Wavelet Transformation And Application

The image compression algorithms based on Discrete Wavelet Transformation (DWT) can provide ratings according to the image resolution and fidelity (the progressive transmission from lossy to lossless).And it has stronge anti-mistake coder ability, low memory space taken up and fast coding characteristics. Therefore it can availably abate the conflict that the storage and transmission of images in Deep Space Communication (DSC) largely occupy the limited buffer and channel bandwidth of the whole system, and improve the ability that the explorer deals with the images.But compared with common terra and satellite communications, DSC faces more challenges, such as long distance, very low signal noise ratio, high signal propagation delays and data corruption rates, asymmetric bandwidth and so on.Thus, the image compression algorithms based on DWT in the Internet (such as JPEG2000) can not simply apply to DSC.As for it, this paper takes the image compression standards based on DWT that the CCSDS(referred as CCSDS standards) released in 2005 as foundation, studies three dissimilarities of transmitting the images between DSC and the Internet according to user requirements,error containment and data purpose.In the beginning, the CCSDS standards based on DWT is studied in detail.And compared with JPEG2000, although their basic structures are the same, there are different highly about Wavelet Base, DWT Level, Bit Plane Coding and the relativity between the coefficients. As these dissimilarities can lower complications, the power and the usage of the buffer can be lowered on the explorer.Based on studying the special problem that DSC transmit and store compressed bit streams, this paper presentes four methods fit for the characteristic of CCSDS standards.Firstly, the image segmentation method is presented that is fit for the CCSDS standards.It can lower the influence that buffer overload and error propagation of the ground decoder because of receiving error compressed bit streams. The segmentation is carried on after image DWT. After pre-segmentation of the image, each block is divided up and fused again.Each block can keep on be partitioned based on the image features (such as color, band and texture etc.) by Gaussian mixture models. Based on the usage of CPU in the explorer, ICM and naive Bayes can be selected to finish the segmentation together.The results are verified by simulation.Secondly, the new image compression scheme based on Region of Interest (ROI) is presented that is fit for the CCSDS standards.And according to the Rate- Distortion(R-D) model of CCSDS standards and the method used for voice quantization optimum bit assignment, the optimum bit assignment between ROI and NON Region of Interest (NON-RON) is achieved.Based on the priority partition table of the image and the character of Bit Plane Coding, the opposite position between ROI and NON-ROI is adjusted. Compression rate of each block can be assigned in order to carry out the optimized assignment of transmission bits under the condition of limited and fixed download channel rate. According to the elicitation of the relationship about R-D given by Mallat, R-D model of CCSDS standards is obtained by simulation of several test images.Thirdly, the method fit for CCSDS standards is presented.It divides wavelet coefficients of tree structure to different groups. Based on R-D model of CCSDS standards and the method used for voice quantization optimum bit assignment, the optimum bit assignments between different groupings is achieved.It can not only achieve robust transmission of compressed bit streams, but also make the information of image received by the ground more. It groups the wavelet efficients and produces nine independent and interlaced bit streams, and assigns compression ratio for each group so that total information can be maximized.Finally, the method of the joint decoding between CCSDS standards and Turbo coder is presented. When signal to noise ratio is invariable, the bit error rate of receiving the compressed bit streams can be lowered even if compression coding do not change at all. Such method is especially fit for the deep space communication.By combining the residual redundancy during entropy encoding and the relativity between the different wavelet coefficients of CCSDS standards with the iterative and the usage of extrinsic information during Turbo decoding, joint decoding can be carried out at last.