JPEG2000中的自适应量化研究

根据人类视觉特性和小波子带图像分布特性及子带系数对保存边缘、纹理信息的重要性程度,提出一种基于图像纹理分类的自适应量化编码算法,在同一子带内根据小波系数对保存边缘、纹理信息的重要性程度,将小波高频子带内划出平坦块、纹理块和边缘块,对其采用不同的量化间隔,并以JPEG2000为平台进行了实验.结果证明,采用该算法,可以在低码率下较好地保存图像的边缘和纹理特性的信息,重构图像的主观质量有一定的提高.

Adaptive Quantization in JPEG2000 Framework

In this paper, an adaptive quantization strategy based on image texture classification is proposed. Based on the characteristics of the human vision, the new approach takes into account the statistical characteristics of each subband and the different effects of wavelet coefficients in each subband on saving the edge and texture information of original image. Each high frequency subband is divided into blocks. The blocks are classified as smooth blocks, edge blocks or texture blocks. The wavelet coefficient is quantized adaptively depending on which kind block and subband it belongs to. A specific application of the proposed strategy to JPEG2000 is presented. Experimental results show that this approach can save the edge and texture information well at low bit rate and the subjective quality of the reconstructed image is improved to some extent.