【摘要】 针对传统的线性小波分解不能很好保留图像边缘信息,且在跃变点处会出现大的小波系数而不利于图像压缩,提出了一种新的基于提升方案的二维不可分离自适应小波变换(AWT)方案。在该方案中,根据局部信息自适应地将图像分为平滑区域和非平滑区域,在不同区域选取不同的更新和预测函数。通过在JPEG 2000中的实验结果表明,用该方法进行图像分解,低频近似图像保留了细节信息,边缘清晰;对双边AWT后的图像压缩,性能优于JPEG 2000的5/3小波和9/7小波,峰值信噪比(PSNR)提高0.5~2.0 dB。更多还原

【Abstract】 The traditional linear wavelet decomposition has the drawback that it is not optimally suited to represent edge information.And wavelet coefficients are bigger at transition locations than others,which is disadvantage to image compression.To overcome the problems,a new 2-D nonseparable adaptive wavelet transform(AWT) based on lifting scheme has been presented.In this method,the image is adaptively partitioned into smooth and sharp areas according to local information.Thus the method processes edges and homogeneous image regions in different ways through selecting appropriate update and prediction filters.Experiments in JPEG 2000 show that the edges of image are much more reserved,and the dual AWT precedes 5/3 wavelet and 9/7 wavelet.Moreover,the rate-distortion curves exhibit 0.5-2.0 dB improvement in compression performance.更多还原