Bayer demosaicking using optimised mean curvature over RGB channels. Issue 17 (4th August 2017)

• Record Type: Journal Article
• Authors: Chen, Rui; Jia, Huizhu; Wen, Xiange; Xie, Xiaodong
• Is Part Of: Electronics letters. Volume 53:Issue 17(2017)
• Page Start: 1190
• Page End: 1192
• Publication Date: 2017-08-04
• Subjects: image segmentation -- image resolution -- image colour analysis -- interpolation -- image reconstruction -- image restoration; optimised mean‐curvature model -- RGB channel -- Bayer image demosaicking method -- interpolation -- cross‐channel aliasing -- variational MC model -- G‐image surface restoration -- linear MC model -- image resolution -- image colour analysis; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2017.1892
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : Colour artefacts of demosaicked images are often found at contours due to interpolation across edges and cross‐channel aliasing. To tackle this problem, a novel demosaicking method to reliably reconstruct colour channels of a Bayer image based on two different optimised mean‐curvature (MC) models is proposed. The missing pixel values in green (G) channel are first estimated by minimising a variational MC model. The curvatures of restored G‐image surface are approximated as a linear MC model which guides the initial reconstruction of red (R) and blue (B) channels. Then a refinement process is performed to interpolate accurate full‐resolution R and B images. Experiments on benchmark images have testified to the superiority of the proposed method in terms of both the objective and subjective quality.