Wavelet based Enhanced Color Image Compression relying on Sub-band Vector Quantization

Increase in the use of color images in the continuous expansion of multimedia applications has increased the demand for efficient techniques that can store and transmit visual information. This demand has made image compression a vital factor and has increased the need for efficient algorithms that can result in high compression ratio with minimum loss. This paper proposes an innovative technique for compressing color still images using wavelet compression scheme. The proposed scheme uses wavelet transformation, tree structured vector quantization and binary vector morphological prediction for compressing color images. Binary vector morphology is used to predict the significance of coefficients in the subbands across different color components. The use of tree structured vector quantization reduced the search time for quantization and coding. This greatly enhanced the proposed algorithm in terms of compression and decompression time. The experimental results revealed that the proposed algorithm produced a high compression ratio with minimum loss.