Image enhancement using the image sharpening, contrast enhancement, and Standard Median Filter (Noise Removal) with pixel-based and human visual system-based measurements
{"title":"Image enhancement using the image sharpening, contrast enhancement, and Standard Median Filter (Noise Removal) with pixel-based and human visual system-based measurements","authors":"Erwin, Adam Nevriyanto, D. Purnamasari","doi":"10.1109/ICECOS.2017.8167116","DOIUrl":null,"url":null,"abstract":"In this paper, we explained the three methods of image enhancement: Image Sharpening by sharpening the edges, Contrast Enhancement using Standard Histogram Equalization and Standard Median Filtering where noise is filtered using these methods first and finally noise is eliminated. Then we put on the measurement parameters using a calculation based on the image quality of the pixel MSE and PSNR and calculations based on human vision system (HVS) that SSIM. The dataset we use is BSDS300 Berkeley and the environment is Matlab 2016a. We can state that the image quality measurement is good where the results are accurate so that we can determine the best methods too. We got SSIM value is close to 1 and the value obtained MSE and PSNR is minimum in Image Sharpening which is mean Image Sharpening is best of basic methods in Image Enhancement.","PeriodicalId":6528,"journal":{"name":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","volume":"6 1","pages":"114-119"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Electrical Engineering and Computer Science (ICECOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECOS.2017.8167116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
In this paper, we explained the three methods of image enhancement: Image Sharpening by sharpening the edges, Contrast Enhancement using Standard Histogram Equalization and Standard Median Filtering where noise is filtered using these methods first and finally noise is eliminated. Then we put on the measurement parameters using a calculation based on the image quality of the pixel MSE and PSNR and calculations based on human vision system (HVS) that SSIM. The dataset we use is BSDS300 Berkeley and the environment is Matlab 2016a. We can state that the image quality measurement is good where the results are accurate so that we can determine the best methods too. We got SSIM value is close to 1 and the value obtained MSE and PSNR is minimum in Image Sharpening which is mean Image Sharpening is best of basic methods in Image Enhancement.