Image Coding Using Vector Quantization Based on Discrete Cosine Transform and Run-Length Compensated

Image coding requires a small bit rate for high-speed data transmission and a small space for data storage. Simultaneously, the peak signal to noise ratio (PSNR) has to be maintained. In this paper, first algorithm we present a method of image coding design using wavelet transform (WT). By applying the WT for defining groups of pixels with the same intensity in spatial domain, the groups of pixels are allocated in a low frequency range. Hence, locations of pixels are the key factor to determine the size of each block. And then spend wavelet transform to decompose each block into sub-band components, which are represented by 3D vectors. The 3D vectors are then classified into 8 groups corresponding to quadrants of spatial coordinates. Second algorithm we propose system error compensation on Vector Quantization (VQ) watchdog energy contents of the all sub-bands is used Discrete Cosine Transform. Also coefficient encode/decode by Run-Length coding, is spending. The reconstructed image and system error compensate will be combined in order to construct an output image (Xo). By applying the proposed method, performance of the method is evaluated as 26.19% of bit rate and 1.75% of PSNR improved from the conventional method.