الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
Multispectral image is a collection of several monochrome images of the same scene each image is referred to as a band, each of them taken with a different sensor sensitive to a different wavelength. Multi-spectral images are most commonly used for a large number of applications, such as geology, agriculture, meteorology, pollution monitoring, detection and identification of the surface and atmospheric, analysis of soil type, and military surveillance, for multispectral images, where the amount of data increases with increasing the number of bands, so there is a large amount of data that have to be transmitted, processed, and stored efficiently, these problems can be significantly reduced by using some form of data compression. There are several well-known image compression techniques. The most common ones as in the literature are: the Joint Photographic Experts Group (JPEG), JPEG 2000 and Set Partitioning In Hierarchical Trees (SPIHT). These techniques give a good compression performance. However, they suffer from some weakness such as low quality, and don’t reduce the spectral redundancy, In this thesis, an efficient multispectral image compression technique aiming at reducing the size of storage of multispectral images with high quality reconstruction, this techniques is a hybrid scheme based on the predictors used by lossless JPEG and Set Partitioning In Hierarchical Trees (SPIHT) algorithm after that the compressed image is transmitted over wireless channel using an Orthogonal Frequency-Division Multiplexing (OFDM) system . where the images are affected by noise, a proposed technique for denoising and compression of multispectral satellite images to remove the effect of noise on the compression process by a filtering layer is presented.