{"title":"用于自然和医学图像的合适质量度量的识别","authors":"K. Thakur, Omkar H. Damodare, A. Sapkal","doi":"10.5121/SIPIJ.2016.7303","DOIUrl":null,"url":null,"abstract":"To assess quality of the denoised image is one of the important task in image denoising application. Numerous quality metrics are proposed by researchers with their particular characteristics till today. In practice, image acquisition system is different for natural and medical images. Hence noise introduced in these images is also different in nature. Considering this fact, authors in this paper tried to identify the suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to develop noise dependent quality metric is also identified in this work.","PeriodicalId":90726,"journal":{"name":"Signal and image processing : an international journal","volume":"11 1","pages":"29-43"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"IDENTIFICATION OF SUITED QUALITY METRICS FOR NATURAL AND MEDICAL IMAGES\",\"authors\":\"K. Thakur, Omkar H. Damodare, A. Sapkal\",\"doi\":\"10.5121/SIPIJ.2016.7303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To assess quality of the denoised image is one of the important task in image denoising application. Numerous quality metrics are proposed by researchers with their particular characteristics till today. In practice, image acquisition system is different for natural and medical images. Hence noise introduced in these images is also different in nature. Considering this fact, authors in this paper tried to identify the suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to develop noise dependent quality metric is also identified in this work.\",\"PeriodicalId\":90726,\"journal\":{\"name\":\"Signal and image processing : an international journal\",\"volume\":\"11 1\",\"pages\":\"29-43\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal and image processing : an international journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/SIPIJ.2016.7303\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and image processing : an international journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/SIPIJ.2016.7303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IDENTIFICATION OF SUITED QUALITY METRICS FOR NATURAL AND MEDICAL IMAGES
To assess quality of the denoised image is one of the important task in image denoising application. Numerous quality metrics are proposed by researchers with their particular characteristics till today. In practice, image acquisition system is different for natural and medical images. Hence noise introduced in these images is also different in nature. Considering this fact, authors in this paper tried to identify the suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to develop noise dependent quality metric is also identified in this work.