A Geometric Method for Optimal Design of Color Filter Arrays

被引:37
|
作者
Hao, Pengwei [1 ,2 ]
Li, Yan [2 ]
Lin, Zhouchen [3 ]
Dubois, Eric [4 ]
机构
[1] Univ London, Dept Comp Sci, London E1 4NS, England
[2] Peking Univ, Ctr Informat Sci, Beijing 100871, Peoples R China
[3] Microsoft Res Asia, Beijing 100190, Peoples R China
[4] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON K1N 6N5, Canada
基金
加拿大自然科学与工程研究理事会; 中国国家自然科学基金;
关键词
Color filter array (CFA); discrete fourier transform (DFT); sampling; multiplexing; demosaicking; DEMOSAICKING; INTERPOLATION;
D O I
10.1109/TIP.2010.2077642
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A color filter array (CFA) used in a digital camera is a mosaic of spectrally selective filters, which allows only one color component to be sensed at each pixel. The missing two components of each pixel have to be estimated by methods known as demosaicking. The demosaicking algorithm and the CFA design are crucial for the quality of the output images. In this paper, we present a CFA design methodology in the frequency domain. The frequency structure, which is shown to be just the symbolic DFT of the CFA pattern (one period of the CFA), is introduced to represent images sampled with any rectangular CFAs in the frequency domain. Based on the frequency structure, the CFA design involves the solution of a constrained optimization problem that aims at minimizing the demosaicking error. To decrease the number of parameters and speed up the parameter searching, the optimization problem is reformulated as the selection of geometric points on the boundary of a convex polygon or the surface of a convex polyhedron. Using our methodology, several new CFA patterns are found, which outperform the currently commercialized and published ones. Experiments demonstrate the effectiveness of our CFA design methodology and the superiority of our new CFA patterns.
引用
收藏
页码:709 / 722
页数:14
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