Classification-based de-mosaicing for digital cameras

Ur Rehman, Amin and Shao, Ling (2012) Classification-based de-mosaicing for digital cameras. Neurocomputing, 83. pp. 222-228. ISSN 0925-2312

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Abstract

In this paper, we propose a content adaptive demosaicing algorithm, utilising content analysis and correlation between the red, green and blue planes of a particular image. These two aspects are used for the classification of the technique in the generated trained filters. The proposed method aims to reconstruct a high quality demosaiced image from a CFA Bayer pattern. The strategy highlighted in this paper is very effective, as many of the image details are maintained during reconstruction. Since image content analysis and filter coefficient optimisation are performed during training and the training process is offline, the online de-mosaicing filter is very efficient.

Item Type:	Article
Uncontrolled Keywords:	Bayer pattern; Demosaic; CFA array; RGB; Classification; Trained filter
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Related URLs:	Publisher
Depositing User:	Paul Burns
Date Deposited:	10 Jun 2015 15:11
Last Modified:	12 Oct 2019 22:30
URI:	http://nrl.northumbria.ac.uk/id/eprint/22844

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