一种基于形态学的小波域静态图像编码算法

A New Still Image Coding Algorithm Based on Morphology

零树小波编码器EZW和SPIHT是近年来最优秀的两个编码算法,不足之处在于其表示父子关系使用了较多的辅助位.基于形态学表示的编码器MRWD是另一成功的编码算法,其不足之处在于没有利用带间小波系数相似性.利用这些编码器的优点,并基于小波数据的形态学表示,开发了一个新的高效小波编码器.新的编码算法的主要特点在于充分利用了带内小波系数的聚类特性和带间小波系数的相似性以及幅值衰减性.最突出的特点是利用形态算子和带间相似性进行聚类预测,从而克服了前述3个编码器的不足.具体数值实验结果表明,该算法的编码效率优于上述3类编码器,尤其对于含有大量纹理区域的复杂图像,编码效率的提高尤其显著.例如,对于512×512Barbara图像,在0.25b/p,新算法比EZW,SPIHT和MRWD算法的峰值信噪比（PSNR）分别提高1.68dB,0.87dB和0.59dB.

Zerotree-Based wavelet coders, EZW and SPIHT, are two excellent coding algorithms currently, but the imperfect point is that they need more bits to express the parent-children relationship. The another coder based on the morphological representation of wavelet data (MRWD) is also successful, but the shortage is that it doesn't use the interband similarity of wavelet coefficients. In this paper, a new wavelet-based coder is developed by taking the advantages of the above coders and based on morphology. The main property of the new coder is that it uses following characteristics of wavelet coefficients: (1) within-subband clustering of significant coefficients; (2) cross-subband similarity; (3) decay of magnitude of wavelet coefficients across subband. The advantage of the new coder is to utilize the property of intraband clustering and interband similarity to predict the interband clusters based on morphological operator and then to overcome the shortages of the above three coders. Experimental results show that the performance of the new coder is superior to the above three coders. In specially, the new coder has the outstanding performance for the images including a large portion of texture. For example, for Barbara image 512×512, at 0.25b/p, the new coder outperforms EZW, SPIHT and MRWD by 1.68dB, 0.87dB, and 0.59dB.