{"title":"一种新的无参考图像质量度量,利用物体可分离性来确定给定图像的质量","authors":"K. De, V. Masilamani","doi":"10.1109/MVIP.2012.6428768","DOIUrl":null,"url":null,"abstract":"The goal of researchers in the field of Image Quality Assessment is to quantify quality of an image using a mathematical measure and to design algorithms for computing the measure. The traditional method of doing this involves taking a reference image and a test image of same scene and find differences between the two images. As human eye can differentiate between a good quality image and a distorted one without the use of reference image, in this paper we propose a no-reference image quality measure which will differentiate between a good image and distorted image by calculating certain properties of images based on object separability in the image.","PeriodicalId":170271,"journal":{"name":"2012 International Conference on Machine Vision and Image Processing (MVIP)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A new no-reference image quality measure to determine the quality of a given image using object separability\",\"authors\":\"K. De, V. Masilamani\",\"doi\":\"10.1109/MVIP.2012.6428768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of researchers in the field of Image Quality Assessment is to quantify quality of an image using a mathematical measure and to design algorithms for computing the measure. The traditional method of doing this involves taking a reference image and a test image of same scene and find differences between the two images. As human eye can differentiate between a good quality image and a distorted one without the use of reference image, in this paper we propose a no-reference image quality measure which will differentiate between a good image and distorted image by calculating certain properties of images based on object separability in the image.\",\"PeriodicalId\":170271,\"journal\":{\"name\":\"2012 International Conference on Machine Vision and Image Processing (MVIP)\",\"volume\":\"136 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Machine Vision and Image Processing (MVIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MVIP.2012.6428768\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVIP.2012.6428768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new no-reference image quality measure to determine the quality of a given image using object separability
The goal of researchers in the field of Image Quality Assessment is to quantify quality of an image using a mathematical measure and to design algorithms for computing the measure. The traditional method of doing this involves taking a reference image and a test image of same scene and find differences between the two images. As human eye can differentiate between a good quality image and a distorted one without the use of reference image, in this paper we propose a no-reference image quality measure which will differentiate between a good image and distorted image by calculating certain properties of images based on object separability in the image.