Hybrid vector quantization

Abstract

Vector quantization (VQ) is a powerful technique for low-bit-rate image coding. However, initial studies of image coding with VQ have revealed that VQ causes degradations, most notably around edges. Moreover, the computational complexity is high. Although a few algorithms have been developed to reduce edge degradation, such as block truncation coding (BTC) with VQ (BTCNQ) or classified vector quantization, their compression ratios are not satisfactory. Discrete cosine transformation with VQ (DCTNQ) has been applied to image compression, showing a high compression ratio, but the edge degradation problem still exists. We present an image compression algorithm that takes advantage of the merits of DCTNQ and BTCNQ to achieve a high-quality and low-bit-rate compression of images. High quality images can be achieved at rates of 0.34 to 0.46 bit/pixel.