Nenad Stojanović, Boban P. Bondzulic, B. Pavlović, V. Ristić
{"title":"Contrast Quality Measure: Full-Reference Image Quality Assessment Metric for Infrared Images","authors":"Nenad Stojanović, Boban P. Bondzulic, B. Pavlović, V. Ristić","doi":"10.23919/NTSP54843.2022.9920403","DOIUrl":null,"url":null,"abstract":"The paper proposes an objective image quality assessment measure with full referencing. The measure is based on a comparison of the contrast of the original image and the image with the degradation. Discrete cosine transform coefficients are used for contrast estimation. By applying the measure, a scalar value is obtained that reflects the quality of the test (degraded) image. The proposed measure is tested on an infrared image dataset developed by the Military Academy in Belgrade, Serbia. The performance of the measure was compared with other well-known objective full-reference image quality assessment metrics, which were developed for the images in visible domain. It was shown that measure performance can be improved with the adequate selections of the block dimensions and the number of discrete cosine transform coefficients during the calculation of image quality value. The proposed measure obtained a correlation with the subjective scores near 82%, which puts the measure into the top three of all tested image quality assessment measures. The proposed measure showed the best performance on the images distorted by Gaussian blurring, where the level of agreement with the subjective scores is over 97%, according to which the measure stands out as the best compared to other tested measures.","PeriodicalId":103310,"journal":{"name":"2022 New Trends in Signal Processing (NTSP)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 New Trends in Signal Processing (NTSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/NTSP54843.2022.9920403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper proposes an objective image quality assessment measure with full referencing. The measure is based on a comparison of the contrast of the original image and the image with the degradation. Discrete cosine transform coefficients are used for contrast estimation. By applying the measure, a scalar value is obtained that reflects the quality of the test (degraded) image. The proposed measure is tested on an infrared image dataset developed by the Military Academy in Belgrade, Serbia. The performance of the measure was compared with other well-known objective full-reference image quality assessment metrics, which were developed for the images in visible domain. It was shown that measure performance can be improved with the adequate selections of the block dimensions and the number of discrete cosine transform coefficients during the calculation of image quality value. The proposed measure obtained a correlation with the subjective scores near 82%, which puts the measure into the top three of all tested image quality assessment measures. The proposed measure showed the best performance on the images distorted by Gaussian blurring, where the level of agreement with the subjective scores is over 97%, according to which the measure stands out as the best compared to other tested measures.