Academic Journal

NO-REFERENCE IMAGE QUALITY MEASURE FOR IMAGES WITH MULTIPLE DISTORTIONS USING RANDOM FORESTS FOR MULTI METHOD FUSION

التفاصيل البيبلوغرافية
العنوان: NO-REFERENCE IMAGE QUALITY MEASURE FOR IMAGES WITH MULTIPLE DISTORTIONS USING RANDOM FORESTS FOR MULTI METHOD FUSION
المؤلفون: Kanjar De, Masilamani V
المصدر: Image Analysis and Stereology, Vol 37, Iss 2, Pp 105-117 (2018)
بيانات النشر: Slovenian Society for Stereology and Quantitative Image Analysis, 2018.
سنة النشر: 2018
المجموعة: LCC:Medicine (General)
LCC:Mathematics
مصطلحات موضوعية: human visual system (HVS), image quality assessment (IQA), multiply distorted images, no-reference image quality assessment (NR-IQA), Medicine (General), R5-920, Mathematics, QA1-939
الوصف: Over the years image quality assessment is one of the active area of research in image processing. Distortion in images can be caused by various sources like noise, blur, transmission channel errors, compression artifacts etc. Image distortions can occur during the image acquisition process (blur/noise), image compression (ringing and blocking artifacts) or during the transmission process. A single image can be distorted by multiple sources and assessing quality of such images is an extremely challenging task. The human visual system can easily identify image quality in such cases, but for a computer algorithm performing the task of quality assessment is a very difficult. In this paper, we propose a new no-reference image quality assessment for images corrupted by more than one type of distortions. The proposed technique is compared with the best-known framework for image quality assessment for multiply distorted images and standard state of the art Full reference and No-reference image quality assessment techniques available.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1580-3139
1854-5165
Relation: https://www.ias-iss.org/ojs/IAS/article/view/1534; https://doaj.org/toc/1580-3139; https://doaj.org/toc/1854-5165
DOI: 10.5566/ias.1534
URL الوصول: https://doaj.org/article/9b03c408d98a4787a4d93ebaac0ccf17
رقم الانضمام: edsdoj.9b03c408d98a4787a4d93ebaac0ccf17
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15803139
18545165
DOI:10.5566/ias.1534