自适应中值滤波和小波变换在东巴手稿图像去噪中的应用

2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI) Pub Date : 2017-10-01 DOI:10.1109/ICEMI.2017.8265810

Geng Qiaoman, Wu Guoxin, Xu Xiaoli

{"title":"自适应中值滤波和小波变换在东巴手稿图像去噪中的应用","authors":"Geng Qiaoman, Wu Guoxin, Xu Xiaoli","doi":"10.1109/ICEMI.2017.8265810","DOIUrl":null,"url":null,"abstract":"The images are mixed with a variety of noises in the process of the Dongba Manuscripts digitization. The mixture of Gauss noise and impulse noise is mainly contained in these images. However, the majority of available algorithms can only be implied in removing single noise. As for this situation, a method combining adaptive median filter and wavelet transform is put forward to the noise removal. Meanwhile, simulations are conducted on MATLAB and the result shows that the method can effectively clear the images.","PeriodicalId":275568,"journal":{"name":"2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","volume":"167 3-4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Application of adaptive median filter and wavelet transform to dongba manuscript images denoising\",\"authors\":\"Geng Qiaoman, Wu Guoxin, Xu Xiaoli\",\"doi\":\"10.1109/ICEMI.2017.8265810\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The images are mixed with a variety of noises in the process of the Dongba Manuscripts digitization. The mixture of Gauss noise and impulse noise is mainly contained in these images. However, the majority of available algorithms can only be implied in removing single noise. As for this situation, a method combining adaptive median filter and wavelet transform is put forward to the noise removal. Meanwhile, simulations are conducted on MATLAB and the result shows that the method can effectively clear the images.\",\"PeriodicalId\":275568,\"journal\":{\"name\":\"2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)\",\"volume\":\"167 3-4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEMI.2017.8265810\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMI.2017.8265810","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

东巴手稿数字化过程中，图像混杂着各种杂音。这些图像主要包含高斯噪声和脉冲噪声的混合。然而，大多数可用的算法只能用于去除单个噪声。针对这种情况，提出了自适应中值滤波与小波变换相结合的去噪方法。同时，在MATLAB上进行了仿真，结果表明该方法可以有效地清除图像。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Application of adaptive median filter and wavelet transform to dongba manuscript images denoising

The images are mixed with a variety of noises in the process of the Dongba Manuscripts digitization. The mixture of Gauss noise and impulse noise is mainly contained in these images. However, the majority of available algorithms can only be implied in removing single noise. As for this situation, a method combining adaptive median filter and wavelet transform is put forward to the noise removal. Meanwhile, simulations are conducted on MATLAB and the result shows that the method can effectively clear the images.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI)

自引率

0.00%

发文量