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.
