The Performances Analysis of Fast Efficient Lossless Satellite Image Compression and Decompression for Wavelet Based Algorithm
In recent years the satellite communication has been growing for the development of rapid and efficient techniques for the storage and transmission of satellite images. The science of reducing the number of bits required to represent the image is called image compression. The aim of this paper is to reduce the size of the image, while transmitting the original image. This reduced image is called as compressed image. The compressed image is being transmitted and it is reconstructed in the receiving side so that the compressed image is being decompressed to obtain the original image. And also transmission of such satellite image increases communication accuracy but requires less bandwidth. In most systems, the amount of intimation that the user wishes to communicate or store necessities some form of compression for efficient and reliable use of communication or storage system. Although several well-known compression techniques exist, many of them require computationally intensive algorithm. In addition to that many compression techniques introduce unwanted attribute such as loss of intimation. This is a major problem in satellite imaging where image degradation may be critical. By considering the above, this paper is to use the wavelet to improve the compression ratio as well as visual quality which is implemented by the famous algorithm called sub band coding and decoding algorithm in MATLAB 7.1 software tool.
image compression satellite communication compression ratio wavelet transform filters image decompression