基于边缘自适应小波变换的低比特率图像压缩算法

常规的小波压缩算法在低比特率情况下将不可避免地在图像强边缘附近产生振铃效应。为此提出了一种基于边缘自适应小波变换的低比特率图像压缩算法。在编码端，先检测出图像的强边缘并将其作为附加信息进行编码；然后，利用强边缘信息将图像沿行列方向分割成一些独立的数据段分别进行小波变换；最后，利用EBCOT算法对得到的小波系数进行编码。特别地，从图像的成像机理出发，提出了一种克服分段数据边界效应的新方法。实验结果表明，这种边缘自适应小波变换即使在比特率极低的情况下也可以保持图像轮廓的清晰，强边缘附近的振铃效应也得到有效的抑制。由于附加信息的存在，压缩图像的PSNR值相比于常规方法通常会有所降低，但图像的主观视觉质量却有明显的提高。

Low Bit Rate Image Compression Based on Edge Adaptive Wavelet Transform

At low bit rate, the images encoded by standard wavelet coders inevitably undergo the so called ringing phenomena near sharp edges. A low bit rate image compression algorithm based on edge adaptive wavelet transform is proposed. At the encoder side, firstly the strong edges of an image are detected and encoded as additional information; Then the wavelet transform is carried out in such a way that no filtering over previously detected edges is performed; Finally, the wavelet coefficients are encoded by the wel known EBCOT algorithm. Especially, a new method to overcome the boundary effects in wavelet transform of segmented data is proposed. Compression examples show that the edge adaptive wavelet transform achieves good reproduction of sharp edges even at very low bit rate. Because of the additional information, the PSNR of the compressed images is typically slightly lower than that of standard coders, but the subjective vision impression is improved significantly.