{"title":"基于bmd的逐像素维纳滤波超声图像散斑去除技术","authors":"Bhawna Gupta, V. Khandelwal","doi":"10.15598/AEEE.V19I2.4100","DOIUrl":null,"url":null,"abstract":"In this paper, an improved Bidimensional Empirical Mode Decomposition (BEMD) based speckle reduction technique for ultrasound images has been proposed. The noisy image has been decomposed into its Intrinsic Mode Functions (IMFs) and a~residue. The noise component of the low order IMFs is removed with the pixel-wise Wiener filtering. The image is reconstructed with these filtered low order IMFs, high order IMFs and the residue. The performance of the proposed method has been tested on synthetic as well as real ultrasound images having noise components of different variance. The experimental results show that the proposed algorithm performs better than other existing methods for synthetic images as well as real ultrasound images in terms of various image quality matrices.","PeriodicalId":7268,"journal":{"name":"Advances in Electrical and Electronic Engineering","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BEMD Based Ultrasound Image Speckle Reduction Technique Using Pixel-Wise Wiener Filtering\",\"authors\":\"Bhawna Gupta, V. Khandelwal\",\"doi\":\"10.15598/AEEE.V19I2.4100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an improved Bidimensional Empirical Mode Decomposition (BEMD) based speckle reduction technique for ultrasound images has been proposed. The noisy image has been decomposed into its Intrinsic Mode Functions (IMFs) and a~residue. The noise component of the low order IMFs is removed with the pixel-wise Wiener filtering. The image is reconstructed with these filtered low order IMFs, high order IMFs and the residue. The performance of the proposed method has been tested on synthetic as well as real ultrasound images having noise components of different variance. The experimental results show that the proposed algorithm performs better than other existing methods for synthetic images as well as real ultrasound images in terms of various image quality matrices.\",\"PeriodicalId\":7268,\"journal\":{\"name\":\"Advances in Electrical and Electronic Engineering\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2021-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Electrical and Electronic Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15598/AEEE.V19I2.4100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Electrical and Electronic Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15598/AEEE.V19I2.4100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
BEMD Based Ultrasound Image Speckle Reduction Technique Using Pixel-Wise Wiener Filtering
In this paper, an improved Bidimensional Empirical Mode Decomposition (BEMD) based speckle reduction technique for ultrasound images has been proposed. The noisy image has been decomposed into its Intrinsic Mode Functions (IMFs) and a~residue. The noise component of the low order IMFs is removed with the pixel-wise Wiener filtering. The image is reconstructed with these filtered low order IMFs, high order IMFs and the residue. The performance of the proposed method has been tested on synthetic as well as real ultrasound images having noise components of different variance. The experimental results show that the proposed algorithm performs better than other existing methods for synthetic images as well as real ultrasound images in terms of various image quality matrices.