Title: A hybrid image compression scheme using HVS characteristics: combining SPIHT- and SOFM-based vector quantisation
Authors: Chandan Singh D. Rawat; Sukadev Meher
Addresses: Electronics and Communication Engineering Department, National Institute of Technology, Rourkela 769008, Orissa, India ' Electronics and Computer Engineering, National Institute of Technology, Rourkela 769008 Orissa, India
Abstract: Nowadays, developing hybrid schemes for effective image compression has gained enormous popularity among researchers. A hybrid scheme combining Kohonen's Self Organising Feature Map (SOFM) based Vector Quantisation (VQ) coding and Set Partitioning In Hierarchical Trees (SPIHT) coding for effective compression of images is proposed. This paper embeds Human Visual System (HVS) into SPIHT algorithm to proffer different perceptual weights to different image blocks. The SPIHT coder results with a bit stream, which is then fed to the SOFM, based VQ coding for compression. The experimental results demonstrate the improvement in CR and subjective visual quality of the images on reconstruction.
Keywords: image compression; human visual system; human visual characteristics; entropy; variance; SPIHT; set partitioning in hierarchical trees; biorthogonal wavelet; vector quantisation; SOFM; self-organising feature map; compression ratio; image processing; visual quality; image quality; image reconstruction.
International Journal of Signal and Imaging Systems Engineering, 2012 Vol.5 No.3, pp.175 - 186
Available online: 17 Oct 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article