Dissertation > Industrial Technology > Automation technology,computer technology > Remote sensing technology > Interpretation, identification and processing of remote sensing images > Image processing methods

Application of Integer Wavelet Transform to Compression of Remote Sensing Images

Author ZhengHua
Tutor LuoJianShu
School National University of Defense Science and Technology
Course Applied Mathematics
Keywords Integer Wavelet Transform Data Compression Statistical properties Remote sensing image Moment estimation
Type Master's thesis
Year 2003
Downloads 196
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Increasingly large amount of remote sensing data , the contradiction between the needs of limited channel capacity and the transmission of large amounts of remote sensing data have become increasingly prominent . Currently, one of the wavelet transform image compression coding technology , more and more attention in the field of remote sensing . In this paper, the integer wavelet transform and its applications in remote sensing image compression , the main results are : first , the statistical characteristics of the remote sensing images by integer wavelet decomposition of the wavelet coefficients in-depth study . Moment estimation, the two high-frequency sub- band distribution parameters obtained numerical characteristics of a sub-sample of the relationship of the shape parameter , and use this formula to estimate the shape parameter , and ultimately determine the distribution . Pearson x ~ 2 test on the above distribution of the obtained test results showed that can simulate a distribution of high - frequency sub-band wavelet coefficients . Second, improved the Listless tree set scanning coding algorithm ( LIFTS ) . And through remote sensing image data of a large number of experimental results show that the improved algorithm SPIHT compression performance similar to , but more easily implemented in hardware . Proposed a multi- spectral remote sensing image compression scheme , using three-dimensional integer wavelet transform combined with improved 3D embedded coding LIFTS can achieve lossy or lossless compression . The experiments show that it is a very effective method .

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