Consumer-level digital cameras observe a single value at each pixel. The remaining two channels of a three-channel image are reconstructed through a process called demosaicking. This paper describes a methodology for enhancing current demosaicking methods. Using an iterative relaxation approach from probabilistic AI literature, our empirical results show that we can improve the results of the s...

Digital Still Color Cameras sample the color spectrum using a monolithic array of color filters overlaid on a charge coupled device array such that each pixel samples only one color band. The resulting mosaic of color samples is processed to produce a high resolution color image such that the values of the color bands not sampled at a certain location are estimated from its neighbors. This proc...

Most of the current digital cameras will capture only one color at each of the pixel using a single sensor overlaid with a color filter array (CFA).Inorder to recover a full color image from a mosaic pattern, specific methods will be used to restore the two missing color values at each of the pixels in the Bayer pattern.The restoration process to find out the missing color samples is known as c...

The problem of image demosaicking (or demosaicing) is where an image has been captured through a color filter array (CFA), and the goal is to estimate complete color information at every pixel. This IPOL article describes the image demosaicking method proposed by Gunturk, Altunbasak, and Mersereau in “Color Plane Interpolation Using Alternating Projections.” Given an initial demosaicking, the m...

Most common cameras use a CCD sensor device measuring a single color per pixel. Demosaicking is the interpolation process by which one can infer a full color image from such a matrix of values, thus interpolating the two missing components per pixel. Most demosaicking methods take advantage of inter-channel correlation locally selecting the best interpolation direction. The obtained results loo...

The effectiveness of utilizing inter-channel correlation and self-similarity for demosaicking has been reported in many literatures. On the other hand, convolutional neural network (CNN)-based techniques have also proposed to achieve state-of-the-art accuracy. In CNN-based demosaicking, one most important issue is how consider correlations using network. this paper, we propose a novel method th...

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 differen...

In this paper we propose a post-processing pipeline to recover accurately the views (light-field) from the raw data of a plenoptic camera such as Lytro and to estimate disparity maps in a novel way from such a light-field. First, the microlens centers are estimated and then the raw image is demultiplexed without demosaicking it beforehand. Then, we present a new block-matching algorithm to esti...

Joint demosaicking and denoising consists in reconstructing a color image from the noisy raw data output by the sensor of a digital camera. We adopt a variational formulation in which the reconstructed image has minimal total variation under the constraint of consistency with the available measurements. This way, the recovered color image has smooth chrominance but the sharp edges are maintaine...