An Edge-Preserving Wavelet Denoising Method Based on MRF
In this paper, we improve the soft-threshold by using Markov random field (MRF) theory to preserve the edges of images. According to MRF theory, the similarity problem of the edge structure can be transformed into an energy function minimization problem. Through computing all the energies of the edge structures in clique c, we can find the edge structure with the minimum energy, and regard it as the edge structure of this place. In this way, we can gain the edge information of an image. Here we detect the edge of image in wavelet domain. In our method we preserve the wavelet coefficients which belong to edge set; for the other wavelet coefficients, the soft threshold method is applied. Then, we reconstruct the treated wavelet coefficients by using inverse wavelet transform. The experiment result shows that our method is better than the hard threshold and soft threshold method. It will not only smooth away noise, but also preserve the edge of image.
wavlet soft-threshold MRF denoising clique
Yongpeng Zhang Feng Duan Rui Cui
Shaanxi Key Laboratory of Speech & Image Information Processing School of Computer Science, Northwestern Polytechnical University Xian, China
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
67-71
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）