کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
537623 870843 2013 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
MLSIM: A Multi-Level Similarity index for image quality assessment
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
MLSIM: A Multi-Level Similarity index for image quality assessment
چکیده انگلیسی


• Human visual system (HVS) distinguishes the quality of an image mainly according to the details given by low-level gradient information.
• Gradient information of images is segmented into multi levels.
• Riesz transform is utilized to get key features of gradient information.
• Regional mutual information is utilized to combine corresponding coefficients of Riesz transform.

Image quality assessment (IQA) is of great importance to numerous image processing applications, and various methods have been proposed for it. In this paper, a Multi-Level Similarity (MLSIM) index for full reference IQA is proposed. The proposed metric is based on the fact that human visual system (HVS) distinguishes the quality of an image mainly according to the details given by low-level gradient information. In the proposed metric, the Prewitt operator is first utilized to get gradient information of both reference and distorted images, then the gradient information of reference image is segmented into three levels (3LSIM) or two levels (2LSIM), and the gradient information of distorted image is segmented by the corresponding regions of reference image, therefore we get multi-level information of these two images. Riesz transform is utilized to get corresponding features of different levels and the corresponding 1st-order and 2nd-order coefficients are combined together by regional mutual information (RMI) and weighted to obtain a single quality score. Experimental results demonstrate that the proposed metric is highly consistent with human subjective evaluations and achieves good performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 28, Issue 10, November 2013, Pages 1464–1477
نویسندگان
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