Design of practical color filter array interpolation algorithms for digital cameras

Author(s):  
James E. Adams, Jr.
Author(s):  
L.M. Varalakshmi ◽  
R. Sowmiya

Most consumer digital cameras use a single image light sensor which provides color information using color filter array(CFA).This  provided a mosaic images, in which each pixel position contains only one color component in case of Bayer CFA Pattern. This paper produced a CFA hierarchical prediction scheme based on context adaptive coding. In CFA hierarchical scheme, the green pixels were subdivided into two sets .  was encoded by a gray scale conventional method and  was  predicted based on . The red pixels were predicted using both the sets of green pixels and blue pixels were predicted using red and green. The predictors were designed based on direction of the edges in the neighborhood. Using the prediction information, the magnitude of prediction error was also determined and context adaptive arithmetic coding was applied to reduce bits. The simulated results on CFA images showed that the proposed method gives less bits per pixel than the recently developed CFA compression algorithms.


2020 ◽  
Vol 11 (6) ◽  
pp. 1-19
Author(s):  
Chiman Kwan ◽  
Jude Larkin

Color Filter Array (CFA) has been widely used in digital cameras. There are many variants of CFAs in the literature. Recently, a new CFA known as CFA 3.0 was proposed by us and has been shown to yield reasonable performance as compared to some standard ones. In this paper, we investigate the use of inpainting algorithms to further improve the demosaicing performance of CFA 3.0. Six conventional and deep learning based inpainting algorithms were compared. Extensive experiments demonstrated that one algorithm improved over other approaches.


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