Modified vector quantization based image compression technique using wavelet transform

Abstract

In this thesis, an image compression mcthod combining discrctc Wavclct transform (OWT) and vector quantization (YQ) i~ presented. First, a three-level OWT is performed on the original image resulting in ten scparatc subbands. Ten separate codcbooks are gcnerated for ten subbands using four training imagcs. The self-organizing featurc map (SOFM) algorithm is used for the generation of codebook. An error correction scheme is also employed to improve the peak signal to noise ratio (PSNR) of the reconstructcd imagc. Ten crror codcbooks are also generated in the error correction scheme using the difference between the original wavelet coefficicnts and the vector quantized coefficients with SOFM algorithm. The indices of the codebooks are Huffman coded to further increase the compression ratio at the transmission end of the encoder. The proposed scheme shows better image quality in terms of PSNR at the same compression ratio as compared to other OWT and YQ based image compression technique found in the literature. The error correction scheme is an iteration process which continuously checks the image quality after sending the Huffman coded bit stream of the error code book indices through the channel each time. The proposed method will be extremely helpful in situations where high quality data is required at the expense of compression ratio.