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Evaluating Multiexposure Fusion Using Image Information

Rahman, Hisham and Soundararajan, Rajiv and Babu, RV (2017) Evaluating Multiexposure Fusion Using Image Information. In: IEEE SIGNAL PROCESSING LETTERS, 24 (11). pp. 1671-1675.

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Official URL: http://doi.org/10.1109/LSP.2017.2752233


Multiexposure fusion (MEF) refers to image fusion methods that capture high dynamic range natural scenes from a set of low dynamic range camera images. In this letter, we study the problem of designing quality assessment (QA) algorithms to estimate the perceptual quality of images generated by different MEF algorithms. We develop our quality index by evaluating individual quality maps between a given fused test image and individual over-/underexposed images at multiple scales and orientations and then combining these maps across the over-/underexposed images. Our approachworks on the premise that the true undistorted reference is contained across the over-/underexposed source images. We identify this true reference based on the notion of perceived image information using natural scene statistical models. It is shown that our approach outperforms the state of the art QA algorithms in terms of correlation with human perception of quality on a publicly available MEF database.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 30 Oct 2017 03:41
Last Modified: 25 Feb 2019 05:52
URI: http://eprints.iisc.ac.in/id/eprint/58087

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