Bayer filter

Abstract: Image demosaicing is a problem of interpolating full-resolution color images from so-called color-filter-array (CFA) samples Among various CFA patterns, Bayer pattern has been the most popular choice and demosaicing of Bayer pattern has attracted renewed interest in recent years partially due to the increased availability of source codes/executables in response to the principle of "reproducible research" In this article, we provide a systematic survey of over seventy published works in this field since 1999 (complementary to previous reviews22, 67) Our review attempts to address important issues to demosaicing and identify fundamental differences among competing approaches Our findings suggest most existing works belong to the class of sequential demosaicing - ie, luminance channel is interpolated first and then chrominance channels are reconstructed based on recovered luminance information We report our comparative study results with a collection of eleven competing algorithms whose source codes or executables are provided by the authors Our comparison is performed on two data sets: Kodak PhotoCD (popular choice) and IMAX high-quality images (more challenging) While most existing demosaicing algorithms achieve good performance on the Kodak data set, their performance on the IMAX one (images with varying-hue and high-saturation edges) degrades significantly Such observation suggests the importance of properly addressing the issue of mismatch between assumed model and observation data in demosaicing, which calls for further investigation on issues such as model validation, test data selection and performance evaluation

Abstract: Digital cameras sample scenes using a color filter array of mosaic pattern (e.g., the Bayer pattern). The demosaicking of the color samples is critical to the image quality. This paper presents a new color demosaicking technique of optimal directional filtering of the green-red and green-blue difference signals. Under the assumption that the primary difference signals (PDS) between the green and red/blue channels are low pass, the missing green samples are adaptively estimated in both horizontal and vertical directions by the linear minimum mean square-error estimation (LMMSE) technique. These directional estimates are then optimally fused to further improve the green estimates. Finally, guided by the demosaicked full-resolution green channel, the other two color channels are reconstructed from the LMMSE filtered and fused PDS. The experimental results show that the presented color demosaicking technique outperforms the existing methods both in PSNR measure and visual perception.

Abstract: We propose an effective color filter array (CFA) interpolation method for digital still cameras (DSCs) using a simple image model that correlates the R,G,B channels. In this model, we define the constants K/sub R/ as green minus red and K/sub B/ as green minus blue. For real-world images, the contrasts of K/sub R/ and K/sub B/ are quite flat over a small region and this property is suitable for interpolation. The main contribution of this paper is that we propose a low-complexity interpolation method to improve the image quality. We show that the frequency response of the proposed method is better than the conventional methods. Simulation results also verify that the proposed method obtain superior image quality on typical images. The luminance channel of the proposed method outperforms by 6.34-dB peak SNR the bilinear method, and the chrominance channels have a 7.69-dB peak signal-to-noise ratio improvement on average. Furthermore, the complexity of the proposed method is comparable to conventional bilinear interpolation. It requires only add and shift operations to implement.

Abstract: In this paper, we present a fast and high-performance algorithm for color filter array (CFA) demosaicing. CFA demosaicing is formulated as a problem of reconstructing correlated signals from their downsampled versions with an opposite phase. The major contributions of this work include 1) a new iterative demosaicing algorithm in the color difference domain and 2) a spatially adaptive stopping criterion for suppressing color misregistration and zipper artifacts in the demosaiced images. We have compared the proposed demosaicing algorithm with two current state-of-the-art techniques reported in the literature. Ours outperforms both of them on demosaicing performance and computational cost.