NDLI: Night Removal by Color Estimation and sparse representation

Content Provider	IEEE Xplore Digital Library
Author	Huiyuan Fu Huadong Ma Shixin Wu
Copyright Year	2012
Description	Author affiliation: Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China (Huiyuan Fu; Huadong Ma; Shixin Wu)
Abstract	Night Removal is highly desired in both computational photography and computer vision applications. However, few works have been studied towards this goal. This paper proposes an effective algorithm for removing the night from a single input image. We present a new Color Estimation Model (CEM) for transforming the image from “night” to “day” — along with a guided statistical Dark-to-Day (D2D) prior directing for performance optimization. To restore the noisy and blurred image after CEM, sparse representation based on dozens of corresponding day-time images in different illuminations as dictionary training set is used in our algorithm. Extensive experiments on natural images show our algorithm can achieve convincing results.
Starting Page	3656
Ending Page	3659
File Size	519725
Page Count	4
File Format	PDF
ISBN	9781467322164
ISSN	10514651
e-ISBN	9784990644109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-11
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	ICPR Org Committee
Subject Keyword	Image color analysis PSNR Image restoration Transforms Indexes Estimation Noise measurement
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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