Evaluating supervised learning approaches for spatial-domain multi-focus image fusion
نویسندگان
چکیده
منابع مشابه
Multi Focus Image Fusion Using Statistical Approaches
Pictures of the long focal lengths cameras, suffer from the problem of limited depth of field. Consequently, it is often difficult to obtain good focus for all objects in the picture. In this work, the problem of multi focus is solved by taking several pictures with different focus points, and then fusing them together to form a single image using image fusion method. Contrast of the source ima...
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The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced using considering the focus measurement in the spatial domain. However, the multi-focus image ...
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We introduce in this paper a region based multi-focus image fusion algorithm using spatial frequency and genetic algorithm. The basic idea is to divide the source images into blocks, and then select the corresponding blocks with higher spatial frequency value to construct the resultant fused image. GA is brought forward to determine the suitable sizes of the block.
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This paper presents a method for removing focal blur in images using fusion algorithm. Different focal images can be combined to give a single fused image with all focused information. Pattern selective image fusion provides a mechanism for combining multiple images through identifying salient features in the source images and combining those features in to a single fused image. However one of ...
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ژورنال
عنوان ژورنال: DYNA
سال: 2017
ISSN: 2346-2183,0012-7353
DOI: 10.15446/dyna.v84n202.63389