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Problem statement: Uncompressed graphics, audio and video data require considerable&#13; storage capacity and transmission bandwidth. Despite rapid progress in mass-storage density,&#13; processor speeds and digital communication system performance, demand for data storage capacity&#13; and data transmission bandwidth continues to outstrip the capabilities of available technologies. The&#13; recent growth of data intensive digital audio, image and video (multimedia) based web applications,&#13; have not only sustained the need for more efficient ways to encode signals and images but have made&#13; compression of such signals central to signal-storage and digital communication technology.&#13; Approach: The objective includes developing and applying an efficient Space-Frequency&#13; Segmentation (SFS) as an image partitioning scheme, then using an appropriate entropy-coding&#13; algorithm that can be used with the developed segmentation to improve compression performance,&#13; particularly in the case of still image compression. The proposed compression system focuses on an&#13; innovative scheme for adaptive wavelet coding technique combined with spatial encoding.&#13; Result: Experiments conducted using the proposed system produced encouraging results. The entropyspatial&#13; coders used in the proposed system produced better results than those obtained by using the&#13; basic arithmetic coder. It provides more appropriate rate-distortion optimization for the spacefrequency&#13; segmentation than the basic arithmetic coder does. The proposed compression system&#13; implies some control coding parameters; the effects of these parameters were investigated to determine&#13; the suitable range for each one of them. Conclusion: We conclude that a comparison between the&#13; energy of two partitioning types (space and frequency) shows that the energy of frequency partitioning&#13; is greater than the space partitioning from the point of view of quality of compressed image. And also&#13; the selection of parameter value used in SFS part (Ratio and Threshold) should be chosen correctly,&#13; because its value has a great effect on the compressed image quality. And the selection of the&#13; quantization step size and the quantization factor (weight) should be done carefully, because&#13; experimental results show that these two factors have a great effect on the compression ratio and PSNR&#13; factor. Finally experimental results indicate that the use of GAP predictor produces better PSNR than&#13; other predictors

Colored Image Compression Using Gradient Adjustment Prediction Based Wavelet