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Uniform depth region‐based registration between colour channels and its application to single camera‐based multifocusing
Author(s) -
Lee Jinhee,
Paik Joonki
Publication year - 2013
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.2011.0171
Subject(s) - computer vision , artificial intelligence , computer science , single camera , image registration , computer graphics (images) , image (mathematics)
This study presents a spatially varying image registration method based on regions of the same depth. The proposed registration method uses phase correlation matching to measure colour shifting vectors (CSVs) between colour channels in a pre‐specified region of the same distance to the camera, and aligns colour channels of the corresponding region according to the CSV. The authors also present the foreground region detection method by using binary edge labelling and analysis of histograms of channel‐shifting features. The major contribution of this study is 2‐fold: (i) the proposed method can be considered as a region‐wise approximated version of fully non‐rigid registration, which is widely used in the medical imaging area, and (ii) it can compensate misalignment between red (R), green (G) and blue (B) colour channels caused by refraction and chromatic aberration of a multiple colour‐filtered aperture (MCA) camera, which has been proposed as a single camera‐based multifocusing system. Among various applications of non‐rigid image registration, the proposed region‐based registration method is particularly suitable for multifocusing images acquired by an MCA camera. In depth analysis of each step of the proposed algorithm is provided with experimental results, and its application to the MCA camera is also provided to realise efficient depth estimation and highly accurate multifocusing functions using a single camera. Without using joint histogram or geometric transformation, the proposed region‐adaptive approach successfully approximates the fully non‐rigid registration with significantly reduced amount of computation.

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