Colour demosaicking with directional filtering and weighting

Abstract

Digital cameras usually use a single sensor covered with a colour filter array which samples only one colour at the location of each pixel. Restoring a full-colour image by the demosaicking technique is a key task in the digital imaging pipeline. This study proposes a novel demosaicking approach based on the existing directional filtering and weighting techniques. The contributions of this study are two-fold. First, the authors analyse the advantages and limitations of the existing directional filtering and weighting techniques, and improve the two existing techniques in order to suppress the common demosaicking artefacts. Second, the authors give a new estimated scheme for the reconstruction of the colour components. The experimental results show that the proposed method outperforms the recent six state-of-the-art demosaicking methods in terms of both subjective and objective measures.

Example based demosaicing

“…We compare the performance of the suggested EBD algorithm with five state of the art algorithms: DDFW [6], DLMMSE [5], LU [3], AHD [7] and NAT [4]. MATLAB code was kindly provided by authors.…”

“…Li et al [1] surveyed recent demosaicing algorithms and broadly classified them as either spatial-domain [3,4,5,6,7,8] or frequency-domain approaches [9,10]. Li et al showed that even the current state of the art algorithms tend to produce artifacts at high saturated edges and varying hue areas.…”

Demosaicking with two-dimensional continuous 3 × 3 order hidden Markov model

“…Digital imaging devices find a broad range of applications, particularly in digital cameras, surveillance devices, and mobile phones [1][2][3][4][5]. Every pixel must consist of three independent primary color components: red, green, and blue, when a digital camera obtains a color image [1,6].…”

Color Image Enhancement using Subsampled Channel Difference

“…To reduce the cost, currently available digital cameras uses color filter array (CFA) to obtain a color image. Therefore, each pixel only captures one color, and this process is mosaicking, and the opposite process is demosaicking (or color interpolation) [7][8][9]. The opposite process stands for reconstructing missing two colors information.…”