In this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, t

In this paper, an efficient method for compressing color image is presented. It allows progressive transmission and zooming of the image without need to extra storage. The proposed method is going to be accomplished using cubic Bezier surface (CBI) representation on wide area of images in order to prune the image component that shows large scale variation. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, bi-orthogonal wavelet transform is applied to decompose the residue component. Both scalar quantization and quad tree coding steps are applied on the produced wavelet sub bands. Finally, adaptive shift coding is applied to handle the remaining statistical redundancy and attain e

In this work a fragile watermarking scheme is presented. This scheme is applied to digital color images in spatial domain. The image is divided into blocks, and each block has its authentication mark embedded in it, we would be able to insure which parts of the image are authentic and which parts have been modified. This authentication carries out without need to exist the original image. The results show the quality of the watermarked image is remaining very good and the watermark survived some type of unintended modification such as familiar compression software like WINRAR and ZIP

There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja