Image Denoising Based on adaptive Morphological Edge Detection and Wavelet Fusion | |
Gao L(高亮); Ma Y(马钺); Chen S(陈帅); Wu JH(吴景辉) | |
2019 | |
会议日期 | July 12-14, 2019 |
会议地点 | Shenyang, China |
关键词 | Wavelet transform adaptive morphological edge detection wavelet fusion improved wavelet threshold denoising |
页码 | 476-482 |
英文摘要 | The effect of traditional wavelet denoising algorithms is not very good and the detail precision of the image isn't high enough. What is worse, it will damage the edge and corner information of the image, and lose texture details. To solve problems above, a new method based on adaptive morphological edge detection and wavelet fusion is proposed. Firstly, the noisy image is decomposed with two wavelet bases. Then we divide the wavelet coefficients into two parts by using the adaptive morphological edge detection method. Secondly, we deal the wavelet coefficients of the edge by using the improved threshold and the hard threshold function. Thirdly, we deal the others by using the improved wavelet threshold and the improved threshold function. At last, we obtain the denoising image by using the wavelet fusion algorithm. Results of the experiment show that the new method can not only highlight the characteristics of the image texture, but also can remove the noise without hurting the important characteristics and the texture edges at the same time. So the new method has great application value |
产权排序 | 1 |
会议录 | 2019 IEEE International Conference on Power, Intelligent Computing and Systems, ICPICS 2019 |
会议录出版者 | IEEE |
会议录出版地 | New York |
语种 | 英语 |
ISBN号 | 978-1-7281-3720-9 |
内容类型 | 会议论文 |
源URL | [http://ir.sia.cn/handle/173321/26189] |
专题 | 沈阳自动化研究所_智能检测与装备研究室 |
通讯作者 | Gao L(高亮) |
作者单位 | Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China |
推荐引用方式 GB/T 7714 | Gao L,Ma Y,Chen S,et al. Image Denoising Based on adaptive Morphological Edge Detection and Wavelet Fusion[C]. 见:. Shenyang, China. July 12-14, 2019. |
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