Application of Integer Wavelet Transform to Compression of Remote Sensing Images
|School||National University of Defense Science and Technology|
|Keywords||Integer Wavelet Transform Data Compression Statistical properties Remote sensing image Moment estimation|
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 .