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A hybrid lossy image compression technique using classified vector quantiser and singular value decomposition is presented for the efficient representation of medical magnetic resonance-brain images. The proposed method is called hybrid classified vector quantisation. It involves a simple yet efficient classifier based gradient method in the spatial domain which employs only one threshold to determine the class of the input image block, and uses three AC coefficients of the discrete cosine transform coefficients to determine the orientation of the block without employing any threshold that results in high fidelity medical compressed images. Singular value decomposition was used to generate the classified codebooks. The proposed technique was benchmarked with JPEG-2000 standard. Simulation results indicate that the proposed approach can reconstruct high visual quality images with higher peak signal-to noise-ratio than the benchmarked technique and also meet the legal requirement of medical images archiving.
Date of Conference: 14-16 Dec. 2009