Abstract
In this paper, we propose an effective directional Bayer color filter array (CFA) demosaicking algorithm based on residual interpolation (RI). The proposed directional interpolation algorithm aims to reduce computational complexity and get more accurate interpolated pixel values in the complex edge areas. We use the horizontal and vertical weights to combine and smooth color difference estimations. Compared with four directional weights in minimized Laplacian residual interpolation, the proposed algorithm not only guarantees the quality of color images but also reduces the computational complexity. Generally, the directional estimations may be inaccurately calculated because of the false edge information in irregular edges. We alleviate it by using a new method to calculate the directional color difference estimations. Experimental results show that the proposed algorithm provides outstanding performance compared with some previous algorithms, especially in the complex edge areas. In addition, it has lower computational complexity and better visual effect.
Highlights
In recent years, many more people choose digital cameras to take pictures
This paper proposes an effective directional residual interpolation algorithm for color image demosaicking based on minimized Laplacian RI (MLRI)
The proposed algorithm is compared with directional linear minimum mean square-error estimation (DLMMSE) [9], LDI-NAT [29], LDI-NLM [29], VDI [18], RI [19], and MLRI [21]
Summary
Many more people choose digital cameras to take pictures. Each digital color image needs at least three color samples at each pixel. The above mentioned nonadaptive algorithms [6,7,8] have lower computational complexity for the CFA, most of them perform color directional interpolation based on the estimated gradient. Based on the directional linear minimum mean square-error estimation (DLMMSE) framework, Zhang and Wu [9] proposed an adaptive algorithm to improve the problem They assumed that the primary difference signals between G and R or G and B channels are low-pass. Chen and Chang [12] detected edge characteristics by comparing color difference in horizontal and vertical directions They used different weighted interpolation to effectively reduce the color artifacts at the edge of the image and enhance the image quality. This paper proposes an effective directional residual interpolation algorithm for color image demosaicking based on MLRI.
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