NDLI: The new improved image blur assessment metrics

Content Provider	IEEE Xplore Digital Library
Author	Gang Liu Fang Yang Yuan Zhang Chencheng She Dongdong Tian Jing Zhang
Copyright Year	2014
Description	Author affiliation: Sch. of Comput. Sci. & Technol., Xidian Univ., Xian, China (Gang Liu; Fang Yang; Yuan Zhang; Chencheng She; Dongdong Tian; Jing Zhang)
Abstract	Image blur assessment has always played an important role in the image quality assessment (IQA). In fact, many methods have been used to measure the blur of an image, but we find that lots of the traditional methods can't effectively compare the blur among images with different contents, leading to the blur measuring more difficult. Recently, we find a perfect method based on the idea that it is difficult for us to find the differences between an already blurred picture and a re-blurred picture based on the former. As a result, Crete et al. use this character of human eyes to assess the blur of an image. and study it carefully. By analyzing the method, though it's good enough, we find some shortcomings of it and propose two improved algorithms based on it: a new blur metric based on the variation of the neighboring differences around edge and a blur metric based on neighboring variation of second difference matrix. The two new methods have been proved that they are all improved to some extent compared with the original algorithm by experiments. Being helpful to the blur assessment, the improved methods are better in veracity, consistency and monotonousness. What's more, they provide a novel perspective to develop blur metrics.
Starting Page	617
Ending Page	621
File Size	388047
Page Count	5
File Format	PDF
ISBN	9781479958351
DOI	10.1109/CISP.2014.7003853
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Image quality Image edge detection Second Difference Matrix Image Blur Assessment Signal processing algorithms Filtering algorithms Filtering theory Indexes Edge No reference
Content Type	Text
Resource Type	Article

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