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Read more >. This work presents an efficient LTP-based sharpness measure for blur detection and segmentation.
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    The defocus or motion effect in images is one of the main reasons for the blurry regions in digital images.

  • The proposed sharpness metric exploits the observation that most local image patches in blurry regions have significantly fewer of certain local binary patterns compared with those in.
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  • LBP-based segmentation of defocus blur computer-vision segmentation markov-random-field blur-detection lbp local-binary-patterns sharpness defocus.
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    Blur, may it be caused by either defocus or by the relative motion between scene and camera, it usually varies spatially in an image, and thus its estimation in a single image becomes a challenging task [1], [2].

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  • LBP-based segmentation of defocus blur.
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    Jointly optimizing the NeRF and the DSK module allows us to restore a sharp NeRF.

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    Update1: The blur maps for the 1000 images in the blur.