S. A. Halim, M. Z. P. Z. Nadila, A. Ibrahim, Y. Manurung
{"title":"带图像质量参数的消噪方法在μ聚焦数字射线图像上的性能","authors":"S. A. Halim, M. Z. P. Z. Nadila, A. Ibrahim, Y. Manurung","doi":"10.1109/BEIAC.2012.6226073","DOIUrl":null,"url":null,"abstract":"This study deals with noise removal methods on radiographic image which acquired using μ-focused digital radiography machine. The purposes of the study are to enhance the quality of radiographic image using noise removal methods and analyze the image quality using error measurement metrics. Median, gaussian, average and circular averaging filters are the noise removal methods applied on original radiographic image to produce processed image. Then, the processed image are measured in terms of Signal to Noise Ratio (SNR), Maximum Absolute Error (MAXABS), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE). Besides that, the image quality is also measured using Modulation Transfer Function (MTF). Results show that gaussian filter gives the best enhancement of image quality based on error metrics and MTF. The development of image enhancement and quality measurement methods implementation are done using MATLAB R2009a.","PeriodicalId":404626,"journal":{"name":"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)","volume":"380 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Performance of noise removal methods with image quality parameter on μ-focused digital radiographic image\",\"authors\":\"S. A. Halim, M. Z. P. Z. Nadila, A. Ibrahim, Y. Manurung\",\"doi\":\"10.1109/BEIAC.2012.6226073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study deals with noise removal methods on radiographic image which acquired using μ-focused digital radiography machine. The purposes of the study are to enhance the quality of radiographic image using noise removal methods and analyze the image quality using error measurement metrics. Median, gaussian, average and circular averaging filters are the noise removal methods applied on original radiographic image to produce processed image. Then, the processed image are measured in terms of Signal to Noise Ratio (SNR), Maximum Absolute Error (MAXABS), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE). Besides that, the image quality is also measured using Modulation Transfer Function (MTF). Results show that gaussian filter gives the best enhancement of image quality based on error metrics and MTF. The development of image enhancement and quality measurement methods implementation are done using MATLAB R2009a.\",\"PeriodicalId\":404626,\"journal\":{\"name\":\"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)\",\"volume\":\"380 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BEIAC.2012.6226073\",\"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 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BEIAC.2012.6226073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance of noise removal methods with image quality parameter on μ-focused digital radiographic image
This study deals with noise removal methods on radiographic image which acquired using μ-focused digital radiography machine. The purposes of the study are to enhance the quality of radiographic image using noise removal methods and analyze the image quality using error measurement metrics. Median, gaussian, average and circular averaging filters are the noise removal methods applied on original radiographic image to produce processed image. Then, the processed image are measured in terms of Signal to Noise Ratio (SNR), Maximum Absolute Error (MAXABS), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE). Besides that, the image quality is also measured using Modulation Transfer Function (MTF). Results show that gaussian filter gives the best enhancement of image quality based on error metrics and MTF. The development of image enhancement and quality measurement methods implementation are done using MATLAB R2009a.