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Demosaicking

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
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평가표
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보존된 평가 기록
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Most modern digital cameras acquire color images by measuring only one color channel per pixel, red, green, or blue, according to a specific pattern called the Bayer pattern. Demosaicking is the processing step that reconstruct a full color image given these incomplete measurements.

Source: Revisiting Non Local Sparse Models for Image Restoration

데이터셋

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PixelShift200

Advanced pixel shift technology is employed to perform a full color sampling of the image. Pixel shift technology takes four samples of the same image at nearly the same time, and physically controls the camera sensor to move one pixel horizontally or vertically at each sampling to capture all color information at each pixel. The pixel shift technology ensures that the sampled images follow the distribution of natural images sampled by the camera, and the full information of the color (R, Gr, Gb, B channel) is completely obtained without any need of interpolation. In this way, the collected RGB images are artifacts-free, which leads to better training results for demosaicing related tasks. PixelShift200 Dataset contains 210 high quality 4K images. - Training: 200 images - Testing: 10 images - Key Features: fully colored, demosiacing artifacts free - Camera: SONY α7R III Source: PixelShift200

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.