Satellite Image Compression Using Dual Tree Complex wavelet Transform

Abstract

Satellite images are composed of multiple bands of data covering a large spectrum of reflected light having some GB of data. For such huge amount of data, image compression is particularly important where the images must be compressed and sent over a limited bandwidth before analysis can take place. For various image processing applications, the wavelet transform is a more effective and powerful tool, but it has some limitations like shift invariance, poor directional selectivity and absence of phase information. Complex wavelet transform overcomes these limitations but perfect reconstruction using complex filter is very complicated. Hence approximate shift variant DT-CWT (Dual Tree Complex Wavelet Transform) is implemented in this paper with redundancy of 4:1. This transform provides approximate shift variance and directionally selective filters along with perfect reconstruction. In this paper very efficient DTCWT based (Set Partitioning In Hierarchical Trees algorithm) SPIHT algorithm optimized for progressive image transmission applied for satellite images is presented. It has been shown that proposed method for image compression gives better result in terms of PSNR and hence the image quality as compare to simple DWT.