{"title":"基于稀疏表示的水下声纳图像去噪方法","authors":"Di Wu, Xue Du, Kaiyu Wang","doi":"10.1109/ICIVC.2018.8492877","DOIUrl":null,"url":null,"abstract":"In order to remove the complex and severe noise from sonar image more effectively, an image denoising approach based on sparse representation is carried out in this paper. To decompose and then reconstruct the sonar image on DCT dictionary with OMP is effective for additive noise removing. Then a logarithmic transformation was applied on the previous reconstructed image to make it adapt to sparse representation denoising model. Experiments are provided to demonstrate the performance of the proposed approach. Results show that this method is efficient in removing additive and multiplicative noise from the sonar image and is also particularly appealing in terms of both denoising effect and keeping details.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"An Effective Approach for Underwater Sonar Image Denoising Based on Sparse Representation\",\"authors\":\"Di Wu, Xue Du, Kaiyu Wang\",\"doi\":\"10.1109/ICIVC.2018.8492877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to remove the complex and severe noise from sonar image more effectively, an image denoising approach based on sparse representation is carried out in this paper. To decompose and then reconstruct the sonar image on DCT dictionary with OMP is effective for additive noise removing. Then a logarithmic transformation was applied on the previous reconstructed image to make it adapt to sparse representation denoising model. Experiments are provided to demonstrate the performance of the proposed approach. Results show that this method is efficient in removing additive and multiplicative noise from the sonar image and is also particularly appealing in terms of both denoising effect and keeping details.\",\"PeriodicalId\":173981,\"journal\":{\"name\":\"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIVC.2018.8492877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIVC.2018.8492877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Effective Approach for Underwater Sonar Image Denoising Based on Sparse Representation
In order to remove the complex and severe noise from sonar image more effectively, an image denoising approach based on sparse representation is carried out in this paper. To decompose and then reconstruct the sonar image on DCT dictionary with OMP is effective for additive noise removing. Then a logarithmic transformation was applied on the previous reconstructed image to make it adapt to sparse representation denoising model. Experiments are provided to demonstrate the performance of the proposed approach. Results show that this method is efficient in removing additive and multiplicative noise from the sonar image and is also particularly appealing in terms of both denoising effect and keeping details.