An adaptive hybrid image compression method and its application to medical images
Ali Al-Fayadh, Abir Jaafar Hussain, Paulo Lisböa, Dhiya Al‐Jumeily · 2008
An efficient adaptive lossy image compression technique using classified vector quantiser and singular value decomposition for compression of medical magnetic resonance-brain images is presented. The proposed method is called adaptive hybrid classified vector quantisation. A simple but efficient classifier based gradient method without employing any threshold to determine the class of the input image block in the spatial domain that results in a high- fidelity medical compressed image was utilised. The proposed technique was benchmarked with JPEG-2000 standard. Simulation results indicated 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 image archiving.