Research on Image Compression and Implementation Using TMS320C6713 Based on SPIHT Algorithm
|School||Harbin Institute of Technology|
|Course||Instrument Science and Technology|
|Keywords||image compression discrete walevelet transform SPIHT DSP|
Digital images are widely used in many fields such as military affairs, civil aspects and social life. As the tremendous original image data is a great challenge to transmission and storage, the image compression becomes necessary. This thesis focuses on the design of the image compression based on Set Partitioning in Hierarchical Trees (SPIHT) algorithm.This thesis first introduces the concepts of image compression and the methods of achieving the pretreatment of image in general. The discrete wavelet transform (DWT) combined with SPIHT coding is adopted as the approach to compression in consideration of efficiency, hardware and software expense, design complexity. In the theory part, lifting scheme, integer 5/3 wavelet transform and wavelet based the algorithm of image compression are introduced, followed by the description of original SPIHT and its modified non-list algorithm. In the part of hardware, the overall scheme is determined according to the requirement of image compression. The design of image data transfer based on SDRAM, data storage, image compression and control based on TMS320C6713DSP and JTAG interface are described in detail. It is the very core of subjcet to achieve the algorithm of image compression.The ideas and implementations to 4-level integer 5/3 wavelet transform and modified SPIHT coding based on DSP are expounded. The program is described in C language which enhances its generality and portability. Pipelining is taken into the parts of compression program design so that the process ability of the system is improved.The approach to image compression is approved by MATLAB simulation and Lab Windows/CVI simulation. Compared with the MATLAB result, the wavelet transform and SPIHT coding program is analyzed after simulation based on DSP. The result based on hardware confirms the program runs as expected and the card is capable of processing images with 512×512 pixels, achieving relatively high compression ratio with image quality loss in a limited range.