{"title":"基于梯度直方图的模糊图像质量评价方法","authors":"Sangwoo An, Jongjoo Park, J. Chong","doi":"10.1145/2526188.2526226","DOIUrl":null,"url":null,"abstract":"In this paper we propose a blurring image quality assessment (IQA) based on histogram of oriented gradients (HOG). The image quality can be determined by the slope value of the HOG of the target image. The representative line of HOG is approximated by a random sample consensus set (RANSAC). Simulation results performed on the LIVE image quality assessment database show that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.","PeriodicalId":114454,"journal":{"name":"Brazilian Symposium on Multimedia and the Web","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Blurring image quality assessment method based on histogram of gradient\",\"authors\":\"Sangwoo An, Jongjoo Park, J. Chong\",\"doi\":\"10.1145/2526188.2526226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose a blurring image quality assessment (IQA) based on histogram of oriented gradients (HOG). The image quality can be determined by the slope value of the HOG of the target image. The representative line of HOG is approximated by a random sample consensus set (RANSAC). Simulation results performed on the LIVE image quality assessment database show that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.\",\"PeriodicalId\":114454,\"journal\":{\"name\":\"Brazilian Symposium on Multimedia and the Web\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brazilian Symposium on Multimedia and the Web\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2526188.2526226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brazilian Symposium on Multimedia and the Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2526188.2526226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Blurring image quality assessment method based on histogram of gradient
In this paper we propose a blurring image quality assessment (IQA) based on histogram of oriented gradients (HOG). The image quality can be determined by the slope value of the HOG of the target image. The representative line of HOG is approximated by a random sample consensus set (RANSAC). Simulation results performed on the LIVE image quality assessment database show that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.