کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
529130 869632 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
GridSAR: Grid strength and regularity for robust evaluation of blocking artifacts in JPEG images
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
GridSAR: Grid strength and regularity for robust evaluation of blocking artifacts in JPEG images
چکیده انگلیسی


• A blind blocking artifacts metric robust to block misalignment is proposed.
• Grid strength and regularity are quantified to measure blocking artifacts.
• A weighting function is proposed to account for the characteristics of the HVS.

Images are subject to blocking artifacts when they are compressed using the JPEG standard. Knowing the extent of blocking artifacts is thus necessary for such applications as automatic quality monitoring and restoration. The current blocking artifacts measures are based on a strong prior that the block boundaries are known in advance, which often does not hold in real-world applications. Therefore, their performances degrade significantly when block boundaries are misaligned. To address the problem, this paper presents a robust no-reference blocking artifacts evaluation metric for JPEG images based on grid strength and regularity (GridSAR). The underlying idea is to extract block grids from a JPEG image and quantify the grid image to evaluate the strength of blocking artifacts. To this end, a grid map of blocking artifacts is first extracted from the image in the spatial domain. Then the blocking artifacts of the image are evaluated by quantifying the strength and regularity of the grid image. Furthermore, in order to account for the varying sensitivities of human eyes to the blocking artifacts in smooth and textured areas, a masking function is also proposed. Experimental results on seven popular image quality databases demonstrate that GridSAR achieves the state-of-the-art performance, and is robust to block misalignments.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 30, July 2015, Pages 153–163
نویسندگان
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