Remote Sensing Image Compression Technology Based On Wavelet Transform

With the rapid development of remote sensing technology, the data amount received by remote sensor is dramatically increasing. These abundant data provides valuable information for researching the earth resources, but it is hard to be stored and transmitted.So it is a challenge to research the compressing techniques to satisfy the requirement.Wavelet Analysis is a novel theoryd eveloped during past 20 years.The technique is the great achievement in Harmony Analysis field for about half of this century and is viewed as a milestone in the development history of Fourier analysis. As a new theory of signalanalysis, Wavelet Transform appears the good localization property in time (space) domain and frequency domain, so we obtain an effective mathematicl tool and use it to lots of research fields such as image processing, partner recognition etc. Based on the theory of Wavelet Transform, this thesis focuses on researching the lossless compression algorithm for the remote sensing image.The research works of the thesis are listed as following:(1) Discussed the Specific needs image compression of remote sensing. Summarized the principles and development history of image compression. Discussed the traditional image compression method in detail.(2) Discussed the wavelet transform and development of the theory in image compression.(3) Discussed the three kinds of the most Popular Wavelet encoding method including ECW,SPIHT,EBOCT.and compare the performance of them.And also introduced the image compression standard jpeg2000.(4) In this paper based on wavelet transform ECW remote sening image compress technology is used.It's the first time to use GDAL plus ECW SDK together to compress image, this enhance the coding and compression efficiency.(5) Gray co-occurrence matrix is used to evaluate the compressed image.Breaking the traditional way use the psnr witch based on gray matrix to evaluate a image. (6) Use thr IDL language build a picture-scan systemwitch base on different compression ratio.