Open AccessCorrection of complex purple fringing by green‐channel compensation and local luminance adaptation
Author(s) -
Malik Parveen,
Karthik Kannan
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2019.0732
Subject(s) - luminance , distortion (music) , channel (broadcasting) , computer science , compensation (psychology) , computer vision , artificial intelligence , adaptation (eye) , contrast (vision) , optics , object (grammar) , pipeline (software) , physics , telecommunications , psychology , amplifier , bandwidth (computing) , psychoanalysis , programming language
In natural photography, defects in camera imaging pipeline often result in some form of colour noise or distortion. Nature of this distortion is generally intertwined with scene dependent variables such as positioning, intensity and composition of light source and local object colour reflectivity. One such defect is called purple fringing aberration (PFA). PFA problems are of two types, one of which corresponds to a localised fringing effect near high contrast zones (termed as Isolated PFA or IS‐PFA) and the second which corresponds to a widespread semi‐transparent purple haze over a large part of natural scene (termed as complex PFA or C‐PFA). Much of the PFA‐correction solutions have been driven towards IS‐PFA and very little towards C‐PFA. Based on a premise that in C‐PFA, green channel is heavily suppressed and noisy, while colour information in red and blue channels are largely conserved, authors propose a green‐channel compensation algorithm for restoring true natural colours in fringe affected region. To correct white‐tuft produced by proposed compensation algorithm, they also devise a suitable localised luminance adaptation procedure to equalise perceived changes in luminance profile. Comparisons with state‐of‐the‐art methods devised to combat this purple haze effect yield promising results for a majority of test cases.