Hybrid Classified Vector Quantisation and Its Application to Image Compression
Ali Al-Fayadh, Abir Jaafar Hussain, Paulo Lisböa, Dhiya Al‐Jumeily · 2007
A novel image compression technique using classified vector quantiser and singular value decomposition is presented for the efficient representation of still images. The proposed method is called hybrid classified vector quantisation. A simple but efficient classifier based gradient method which employs only one threshold to determine the class of the input image block that results in a good image quality was utilised. Singular value decomposition method was used for efficient generation of the classified codebooks. The proposed technique was benchmarked with a standard vector quantiser generated using the k-means algorithm, and JPEG-2000. Simulation results indicated that the proposed approach alleviates edge degradation and can reconstruct good visual quality images with higher peak signal-to noise-ratio than the benchmarked techniques.