Multi‐focus image fusion via morphological similarity‐based dictionary construction and sparse representation
نویسندگان
چکیده
منابع مشابه
Regional multifocus image fusion using sparse representation.
Due to the nature of involved optics, the depth of field in imaging systems is usually constricted in the field of view. As a result, we get the image with only parts of the scene in focus. To extend the depth of field, fusing the images at different focus levels is a promising approach. This paper proposes a novel multifocus image fusion approach based on clarity enhanced image segmentation an...
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Optical imaging cameras suffer from the problem of limited depth-of-field of optical lenses, so it is difficult to get an image with all objects in focus. One way to overcome this problem is by using multi-focus image fusion technique, in which several images with different focus points are combined to form a single image with all objects fully focused. So, it is crucial to effectively extract ...
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Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
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We address the multi-focus image fusion problem, where multiple images captured with different focal settings are to be fused into an all-in-focus image of higher quality. Algorithms for this problem necessarily admit the source image characteristics along with focused and blurred feature. However, most sparsity-based approaches use a single dictionary in focused feature space to describe multi...
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ژورنال
عنوان ژورنال: CAAI Transactions on Intelligence Technology
سال: 2018
ISSN: 2468-2322,2468-2322
DOI: 10.1049/trit.2018.0011