Video Compression Based On Wavelet Analysis Method And Realization

Digital information,especially digital video and audio information,always has large amount of data which makes information storage and transportation difficult. So it's necessary to research on and develop novel effective multimedia data compressing method to solve this problem.Wavelet transform(WT) is a kind of domain transform method in image processing which takes human visual and mental systems into consideration. By decomposing original image to multi-resolutions in frequency domain,it provides ideal transform domain for image compression. The object of this article is to research on several wavelet transform based video compressing method and their running properties. We have done the following work:We have designed wavelet transform and zero-tree coding based still image compressing/decompressing programs in MATLAB environment. Zero-coding method is an effective scanning method of wavelet decomposed coefficients,which can eliminate correlation of wavelet coefficients in different resolutions.We have tested wavelet transform and SPIHT coding based still image compression method. SPIHT(Set Partitioning in Hierarchical Trees) method is a more effective wavelet coefficients scanning method originated from zero-tree method. We have designed programs in C language.We have tested multi-resolution motion estimation(MRME) technique to achieve multi-frame compression in MATLAB. In MRME,coding of intra-frame and inter-frame are done in wavelet decomposition domain. MRME costs much less time to perform motion estimation operation compared to block matching motion full search algorithm(FSA).We have applied wavelet transform and SPIHT coding based still image compressing programs on TMS320C6701 for hardware real-time compression. In order to enhance coding/decoding speed,we have rewritten image wavelet decomposition and composition program with C6701 assembly language in which we made use of parallel instructions and pipeline optimizing skill to lessen calculating time. Image data are exchanged between host and DSP evaluation board in a high speed through PCI interface.Experimental results show when image compressing rate is high,decoded image of wavelet transform based compressing method can preserve objects outline well and has no block effect which may appear in DCT block coding technique. Image compression rate can be changed to any given number by modifying parameter of the program. After properly designing,wavelet transform program on DSP has reached C6701's speed limit. As to MRME method,we only did simulation to get its resultant statistics because of time limitation. Simulation results show reconstructed image of this technique has good overall visual effect and has no block profile which may exist in block matching motion estimation method. MRME's time requirement approximates that of block logarithm search algorithm. We concluded that designing DSP andwavelet transform + SPIHT coding + MRME method based video compressing system is applicable. If real-time video data collection part is added,we can get a perfect real time video collecting and compressing system.