An efficient image compression technique using singular value decomposition (SVD) based classified vector quantization (CVQ) and Discrete Sine Transform (DST) for the efficient representation of still images was presented. The proposed method combines the properties of SVD, CVQ, and DST; while avoiding some of their limitations. A simple but efficient classifier based gradient method in the spatial domain, which employs only one threshold to determine the class of the input image block into one

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... of finite number of classes, and uses three AC coefficients of the DST coefficients to determine the orientation of the block without employing any threshold that results in a good image quality was utilized. The proposed technique was benchmarked with the conventional approach based VQ, existing methods using CVQ; and JPEG-2000 image compression techniques. Simulation results indicated that the proposed approach alleviates edge degradation and can reconstruct good visual quality images with higher Peak Signal-to Noise-Ratio (PSNR) than the benchmarked techniques.