Abstract
In this paper, we propose a new demosaicking algorithm which uses eight-directional weights based on the gradient of color difference (EWGCD) for Bayer image demosaicking. To obtain the interpolation of green (G) pixels, the eight-directional G pixel values are first estimated in red (R)/blue (B) pixels. This estimate is used to calculate the color difference in R/B pixels of the Bayer image in diagonal directions. However, in horizontal and vertical directions, the new estimated G pixels are defined to obtain the color difference. The eight-directional weights of estimated G pixels can be obtained by considering the gradient of the color difference and the gradient of the RGB pixels of the Bayer image. Therefore, the eight-directional weighted values and the first estimated G pixel values are combined to obtain the full G image. Compared with six similar algorithms using the same eighteen McMaster images, the results of the experiment demonstrate that the proposed algorithm has a better performance not only in the subjective visual measurement but also in the assessments of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index measurement.
Highlights
Digital color cameras are widely used in our daily life
We propose an eight-directional weighted algorithm based on the gradient of the color difference (EWGCD) for the Bayer image
To demonstrate the effect of the proposed method, the experimental results are compared with directional linear minimum mean square error (DLMMSE) [2], integrated gradients (IG) [6], gradient-based threshold free (GBTF) [8], residual interpolation (RI) [10], minimized-Laplacian residual interpolation (MLRI) [12], and multi-directional weighted interpolation and guide filter (MDWI-GF) [17]
Summary
Digital color cameras are widely used in our daily life. A single image sensor (e.g., CCD or CMOS). Pekkucuksen and Altunbasak [7] suggested an orientation-free edge strength filter, which is used to apply the color difference adaptively in order to provide more edge information They proposed the gradient-based threshold free (GBTF) color filter array interpolation [8], combining estimations from de-coupled directions instead of making a hard direction decision based on the weights. The interpolation method, which defined the residual as the difference between the observed and the tentatively estimated pixel values, first generates an estimate image accurately enough over R/B channel by using the guide filter [11], a powerful edge-preserving filter, followed by using GBTF [8].
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