الفهرس 
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Abstract
Image compression is process to remove the redundant information from the image. So that only essential information can be stored to reduce the storage size, transmission bandwidth and transmission time. The essential information is extracted by various transforms techniques. There are four popular transform techniques which are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Set Partitioning in Hierarchical Trees (SPIHT) and Embedded Zerotree Wavelet (EZW).This thesis presents three hybrid techniques to enhance color image compression techniques. The hybrid techniques are performed on some color images such as Lena, Girl, and Pepper. The first hybrid technique introduces a hybrid (DWT- DCT) with different blocks in DCT because it reduces false contouring, blocking artifacts and ringing effect. The second hybrid technique introduces a hybrid (DCT- SPIHT) technique. It provides higher CR because every image consists of high frequency components and low frequency components. The third hybrid image compression technique uses color based segmentation that segments the image into background and foreground regions and compresses the foreground by DCT. A computer simulation is applied to evaluate the performance of proposed frameworks compared to standalone techniques. The results show that, proposed frameworks perform much better than standalone (DCT, SPIHT, and DWT) techniques in terms of PSNR and CR.