NDLI: Cross-channel regularisation for joint demosaicking and intrinsic lens deblurring

Content Provider	IET Digital Library
Author	Azizi, Reza Latif, Alimohammad
Abstract	Here, the authors present an effective regularisation approach to colour image demosaicking. The authors’ work is inspired by the interesting observation that the cross-channel dependencies of high-frequency details of a colour image are supposed to correspond in all the main colour channels acquired by the sensor. Therefore, minimising their difference in the demosaicking process can significantly improve the quality of the reconstructed image. The authors also demonstrate that mosaicked image formation strictly depends on the intrinsic lens blur. Hence, in the authors’ solution to the image demosaicking as an inverse imaging problem, they take the lens blur characteristics into account. The proposed regularisation method is also based on the fact that sensor saturation significantly alters the distribution of pixel intensity and Gaussian noise. The authors develop an efficient solution to the problem via the alternating direction method of multipliers numerical solver. As a result of these steps, the proposed demosaicking approach significantly enhances the quality of reconstructed images. Experimental results and quantitative evaluations demonstrate that the proposed method outperforms the existing image demosaicking methods.
Starting Page	1683
Ending Page	1691
Page Count	9
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 9, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0743
Journal	IET Image Processing
Publisher Date	2018-04-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Authors Colour Image Computer Vision And Image Processing Technique Cross-channel Dependencies Cross-channel Regularisation Demosaicking Approach Demosaicking Process Effective Regularisation Approach Existing Image Demosaicking Method Filtering Theory Gaussian Noise High-frequency Details Image Colour Analysis Image Reconstruction Image Restoration Image Segmentation Image Sonsor Interesting Observation Intrinsic Lens Blur Intrinsic Lens Deblurring Inverse Imaging Problem Joint Demosaicking Lens Blur Characteristic Main Colour Channel Mosaicked Image Formation Optical Filter Optical, Image And Video Signal Processing Reconstructed Image Regularisation Method Sensor Saturation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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