Techniques for Segementation of Blur Images
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While digital imaging systems have been widely used for many applications including consumer photography, microscopy, aerial photography, astronomical imaging. Their output images/videos often suffer from spatially varying blur caused by lens, transmission medium, post processing algorithms, and camera/object motion. Measuring the amount of blur globally and locally is an important issue. It can help us in removing the spatially varying blur, and enhancing the visual quality of the imaging system outputs. It can also provide useful information about the scene, such as saliency and depth map. A...
While digital imaging systems have been widely used for many applications including consumer photography, microscopy, aerial photography, astronomical imaging. Their output images/videos often suffer from spatially varying blur caused by lens, transmission medium, post processing algorithms, and camera/object motion. Measuring the amount of blur globally and locally is an important issue. It can help us in removing the spatially varying blur, and enhancing the visual quality of the imaging system outputs. It can also provide useful information about the scene, such as saliency and depth map. A technique for defocus map estimation from solitary natural images that estimates the blur amount based on the radius of blurring kernel is used .First it estimate the blur amount at all the locations according to the window mean radius kernel on that position and then a full defocus map can be obtained by propagating the blur amount at all the locations over the entire image.
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