Geometry-Based Demosaicking

Ferradans, Sira; Bertalmío, Marcelo; Caselles, V.

doi:10.1109/tip.2008.2010204

Cited by 23 publications

(2 citation statements)

References 28 publications

(43 reference statements)

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“…As edges may appear anywhere in any direction in an image and have various forms, sharp or soft, strong or weak, long or short, flush or jagged, continuous or fragmental, an edge-sensitive demosaicking method needs to be adaptive and non-linear. In summary, a good demosaicking method should exploit both the spatial and the spectral correlations of a color image and should also consider the discontinuity in the image, such as the edge information [1,5,9,13,18,20,22,27,[39][40][41][42][43][44][45].…”

mentioning

confidence: 99%

Universal Demosaicking of Color Filter Arrays

Zhang

Wang

et al. 2016

IEEE Trans. on Image Process.

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A large number of color filter arrays (CFAs), periodic or aperiodic, have been proposed. To reconstruct images from all different CFAs and compare their imaging quality, a universal demosaicking method is needed. This paper proposes a new universal demosaicking method based on inter-pixel chrominance capture and optimal demosaicking transformation. It skips the commonly used step to estimate the luminance component at each pixel, and thus, avoids the associated estimation error. Instead, we directly use the acquired CFA color intensity at each pixel as an input component. Two independent chrominance components are estimated at each pixel based on the inter-pixel chrominance in the window, which is captured with the difference of CFA color values between the pixel of interest and its neighbors. Two mechanisms are employed for the accurate estimation: distance-related and edge-sensing weighting to reflect the confidence levels of the inter-pixel chrominance components, and pseudoinverse-based estimation from the components in a window. Then from the acquired CFA color component and two estimated chrominance components, the three primary colors are reconstructed by a linear color transform, which is optimized for the least transform error. Our experiments show that the proposed method is much better than other published universal demosaicking methods.

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confidence: 99%

Universal Demosaicking of Color Filter Arrays

Zhang

Wang

et al. 2016

IEEE Trans. on Image Process.

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“…Since each pixel in the image frames of the acquired video has only one of three primary RGB color components, this kind of video is usually referred to as a mosaic video. For a mosaic video, the information about its RGB-CFA structure, which means the arrangement of the RGB color filters in the CFA, is quite important since with this information, the demosaicking process [18], [23], [19], [25], [20], [5], [14], [10], [17], [6], [26], [27] can convert the acquired mosaic video into the full-color video. In general, the RGB-CFA structure information can be obtained from the camera manufacturer or the header of the mosaic video stored in TIFF-EP format.…”

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confidence: 99%

Novel Chroma Subsampling Strategy Based on Mathematical Optimization for Compressing Mosaic Videos With Arbitrary RGB Color Filter Arrays in H.264/AVC and HEVC

Lin

Chung

2016

IEEE Trans. Circuits Syst. Video Technol.

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To save the manufacturing cost, most color digital video cameras employ a single-sensor technology with a redgreen-blue (RGB) color filter array (CFA) to capture the realworld scenes. Due to only one primary color measured at each pixel location, the captured videos are usually referred to as the mosaic videos. For the purposes of economical storage and transmission, it is very important to achieve a good trade-off between the quality and bitrate when compressing mosaic videos with different RGB-CFA structures. In this paper, based on mathematical optimization technique, a novel chroma subsampling strategy is presented for compressing mosaic videos with arbitrary RGB-CFA structures in H.264/AVC and HEVC. For each 2 × 2 YUV block to be subsampled with 4:2:0 format, the proposed strategy determines the proper sampled U and V components by minimizing, prior to compression, the quality distortion between the original co-located mosaic block and the mosaic block conversed from the current subsampled YUV block. Through the mathematical optimization formulated in the proposed strategy, the significance of the sampled U and V components for reconstructing R, G, and B pixels can be simultaneously taken into consideration. Experimental results demonstrate that the proposed chroma subsampling strategy has the best quality and bitrate trade-off at a similar execution-time requirement for compressing mosaic videos with arbitrary RGB-CFA structures in H.264/AVC and HEVC when compared with the state-of-the-art ones by Chen et al. and Yang et al. as well as the three commonly used ones.

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A Patch Aware Multiple Dictionary Framework for Demosaicing

Zhang

Tao

2015

Computer Vision -- ACCV 2014

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Geometry-Based Demosaicking

Cited by 23 publications

References 28 publications

Universal Demosaicking of Color Filter Arrays

Universal Demosaicking of Color Filter Arrays

Novel Chroma Subsampling Strategy Based on Mathematical Optimization for Compressing Mosaic Videos With Arbitrary RGB Color Filter Arrays in H.264/AVC and HEVC

A Patch Aware Multiple Dictionary Framework for Demosaicing

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