小波变换压缩图像的多尺度自适应2D滤波的后处理算法

在基于小波变换的低比特率的图像压缩中，由于小波系数的量化和在高频部分的截断使压缩后的图像呈现出严重的失真，尤其在图像的边缘部分将呈现明显的“振铃效应”．文中提出了一种多尺度、基于局部方向、自适应的2D滤波算法，可以明显改善压缩后图像的视觉效果．该方法首先判定子块内的局部方向，然后根据此方向选用相应的方向2D滤波器滤波．为了保证判断局部方向的鲁棒性，采用了循环移位的方法．为了滤除各个频段的高频噪声，在多个尺度上进行空域滤波．实验结果表明，该算法明显改善了压缩图像的视觉效果，提高了压缩图像的质量．

Postprocessing Algorithm in DWT-Based Image Compression by Using Multiscale Adaptive 2D Filtering

In DWT-based image compression, as the coding rate becomes low, the quality of the coded image degrades severely due to the quantization of wavelet coefficients and the removal of high-frequency wavelet coefficients. Especially, in the vicinity of edges, the ringing effect inevitably comes up. In this paper, a multiscale 2D filtering method based on local primary direction is investigated which may significantly improve the quality of the image compressed. By the method, local primary direction is detected first, according to which the image was filtered adaptively. To ensure the robustness of the detection of the local primary direction, a circular shift method is adopted. To remove the high-frequency noises in all the bands, the decoded image is enhanced from coarse to fine scales. The simulation results illustrate that the method proposed may improve the quality and the visual effect of the compressed images.