In a digital camera usually images are captured using a Color Filter Array (CFA), requiring a demosaicking process to reconstruct the full resolution color image. Often also a denoising step is necessary to remove the noise introduced by the sensor. In this paper we analyze demosaicking and denoising jointly. The color reconstruction is performed using space-varying filters, therefore an evaluation of the autocorrelation of the noise after a space varying filtering is reported. The proposed approach gives good performances and the computational cost is kept low.

Demosaicking is the process of reconstructing a full resolution color image from the sampled data acquired by a digital camera that apply a color filter array to a single sensor. In this paper, we propose a regularization approach to demosaicking, making use of some prior knowledge about natural color images, such as smoothness of each single color component and correlation between the different color channels. Initially, a quadratic strategy is considered and a general approach is reported. Then, an adaptive technique is analyzed, in order to improve the reconstruction near the edges and the discontinuities of the image. This is performed using a novel strategy that avoids computational demanding iterations. The proposed approach provides good performances and candidates itself for many applications. Moreover, since the response of the pixel sensors can be taken into account, it can handle nonideal acquisition devices.

Most color digital cameras apply a color filter array to capture the scene, requiring an interpolation of the subsampled color components to obtain the full resolution image. Therefore, if reconstruction is not performed correctly, noticeable artifacts are produced, which result more evident in the detailed parts of the image. In this paper we propose a demosaicing algorithm based on directional filtering that uses a novel approach to locate the details of the image. To this purpose, edge-estimation is performed on the luminance component of the image in order to give a more reliable information, and the properties of the wavelet transform are used to estimate the edge directions. Experimental results proved the effectiveness of this approach, giving high performance in PSNR, and good estimates of image details too.

Most digital cameras use a color filter array to capture the colors of the scene. Downsampled versions of the red, green, and blue components are acquired, and an interpolation of the three colors is necessary to reconstruct a full representation of the image. This color interpolation is known as demosaicing. The most effective demosaicing techniques proposed in the literature are based on directional filtering and a posteriori decision. In this paper, we present a novel approach to this reconstruction method. A refining step is included to further improve the resulting reconstructed image. The proposed approach requires a limited computational cost and gives good performance even when compared to more demanding techniques.