Stochastic Color Interpolation for Digital Cameras

Abstract

This paper presents a stochastic estimation approach to adaptive interpolation of color filter array. It models an image as a 2-D locally stationary Gaussian process and achieves robustness against aliasing by employing an edge-sensitive weighting policy based on the stochastic characteristics of uniformly oriented edge indicators. Experimental results show that the algorithm can effectively eliminate the occurrence of perceptible artifact. Performance comparison in terms of peak signal-to-noise ratio and mean square error is provided to demonstrate the superiority of the proposed algorithm.Index Terms-Color filter array (CFA), color interpolation, demosaicing, edge detection, edge-sensitive weighting.

Copyright Protection of Color Imaging Using Robust-Encoded Watermarking

“…A threshold value T BER must be defined to determine if the watermark W is present or not into the image. In this concern, considering a binomial distribution with success probability equal to 0.5, the false alarm probability P fa for L bits embedded watermark data is given by (23), and a threshold value T must be controlled in order to get a smaller value of P fa than a predetermined one.…”

“…On the other hand, the normalized color difference (NCD) metric [23], [24] is based on the CIELAB color space and it is applied to measure the difference of color between two images. NCD is given by (27) [23], [24] …”

Digital Color Images Ownership Authentication via Efficient and Robust Watermarking in a Hybrid Domain

“…3 and Fig. 6, it follows that the proposed watermarking algorithm provides a sufficiently good fidelity of the watermarked color image, and also the color difference provided by NCD metric, between the watermarked image and the original one is insignificant [27], i.e., is near to 0.…”

“…The false alarm probability is P fa = 5.6537  10 [25] and Structural Similarity Index (SSIM) [26]. The difference color of the watermarked image is obtained using the Normalized Color Difference (NCD) measure [27]. Finally, we present a comparison with some previously published methods which reported outstanding results and have a similar purpose as our proposal.…”

Novel quality-effective zooming algorithm for color filter array

“…In the first category, these developed nonheuristic demosaicing algorithms include the minimum mean squared error estimator method, 5 the projection-ontoconvex-set method, 6 the linear hyper-plane method, 7 the Fourier domain-based methods, [8][9][10] the wavelet domain method, 11 and the Taylor expansion method. 12 The second category includes the bilinear interpolation method, 13 which is the simplest demosaicing method in which two missing color components of each pixel are calculated by averaging its proper adjacent pixels; the edge-sensingbased methods, [14][15][16][17][18][19][20][21] which can preserve the detailed edge information or limit the hue transitions; the colordifference-based hybrid methods 4,[22][23][24][25][26][27][28][29] in which these methods were developed by integrating the interpolation estimation, edge-sensing scheme, and the color difference technique.…”