Super high definition image coding using successive approximation wavelet vector quantization

Abstract

A method of coding super high definition (SHD) still images based on vector quantization of wavelet coefficients is proposed. In this coding technique, each block of wavelet coefficients is coded by a series of vectors of decreasing magnitudes, resulting in a successive approximation process. It also exploits the structural similarities among the bands. This provides efficient coding together with the ability to guarantee arbitrary distortion levels for each band, which can be exploited to achieve optimum bit allocation. Since SHD images must have high quality, they must be compressed without any visible picture quality deterioration. Due to the huge amount of image data involved, simplicity of the coding system is important to maintain acceptable processing times. Also, a hierarchical structure is desirable to provide compatibility with other existing lower resolution formats, like in multi-media applications. We demonstrate that the proposed method meets these requirements. Conventional image compression techniques such as transform, subband and vector quantization have already been tested for the coding of SHD images. Simulation results show that the proposed method achieves excellent coding performance and it outperforms other SHD image coding methods reported so far by more than 7 dB.