小波图像的膨胀-游程编码算法

Wavelet Image Coding by Dilation-Run Algorithm

提出了一种基于形态膨胀运算和游程编码的新型小波编码器——膨胀-游程(Dilation-Run)算法。编码器根据图像小波变换后重要系数的带内聚类特性和重要系数分布的带间相似性,利用数学形态学中的膨胀运算搜索并编码各聚类中的重要系数;同时使用一种高效的游程编码技术对各聚类的种子系数,即膨胀运算起始点的位置进行编码,从而避免了小波图像中非重要系数的逐个编码。编码器算法简单,并且基于位平面实现,因此输出码流具有渐进性。实验结果表明,膨胀-游程算法的性能优于零树小波编码器SPIHT,并能与两种形态学小波编码器MRWD 和SLCCA的性能媲美。对于聚类特性显著的图像,算法的性能则优于上述形态学小波编码器。

A novel wavelet image coder based on morphological dilation and run-length coding, dilation-run algorithm, is proposed according to both intra-subband clustering of signiflcant wavelet coefflcients and inter-subband dependency in significant fields. The algorithm mainly involves discrete wavelet transform, bit-plane coding, morphological dilation of signiflcant coefficient cluster within subbands, coefficient's significance predicting across subbands, run-length coding of the insignificant coefficients before each seed and adaptive arithmetic coding. The two key features of the algorithm are morphological dilation and run-length coding. The morphological dilation operator is used to search and encode the significant coefficients in each cluster, while a new run-length coding method is used to encode the position of the seed of each cluster, which is the start pixel of the dilation. The dilation-run algorithm, as a kind of embedded coder, is also rate scalable. The experimental results show that the new coder outperforms the zerotree coder SPIHT and is competitive with the morphology coder MRWD and SLCCA. For images with strong clustering feature after the wavelet transform, the new coder outperforms both the morphology coders above.