Paper
8 February 2010 Blurriness estimation in video frames: a study on smooth objects and textures
Author Affiliations +
Proceedings Volume 7532, Image Processing: Algorithms and Systems VIII; 753207 (2010) https://doi.org/10.1117/12.838822
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Abstract
An original blurriness assessment method for video frames is presented. In the first place two measurements are performed uniformly on the whole frame. The first quantifies the perceptive contrast experienced by the human eye, the second uses anisotropic diffusion to estimate a possible detail loss due to blurriness. Secondarily two further indices are devised, each one suitable to a particular sort of image content. The first is dedicated to main, uniform objects, where smoothed borders are deemed to be the main source of blurriness perception. First, a technique is devised to extract all edges, including the smoothest ones. Then the width of such edges is measured, and more weight is given to long than to short ones. The second index measures the activity of textured areas, trying to detect blurriness inside the base texture elements. The four devised indices enable automatic quantification of the strength of blurriness and some hints at its origin. In particular, some new results have been achieved in the ability to automatically distinguish natural blurriness, present in the image content, from undesired one, introduced during encoding and processing.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leonardo Abate, Francesca Dardi, and Giovanni Ramponi "Blurriness estimation in video frames: a study on smooth objects and textures", Proc. SPIE 7532, Image Processing: Algorithms and Systems VIII, 753207 (8 February 2010); https://doi.org/10.1117/12.838822
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Cited by 2 scholarly publications.
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KEYWORDS
Binary data

Computer programming

Edge detection

Video

Image processing

Image quality

Image segmentation

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