On the simplification of multi-focus image fusion using dictionary-based sparse representation

碩士 === 國立中興大學 === 電機工程學系所 === 107 === This paper proposes a fast implementation for multi-focus image fusion using dictionary-based sparse representation. The proposed method reduces the computation complexity of the existing method by synthesizing feature signals from the trained sparse coefficient...

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Main Authors: Chien-an Lin, 林建安
Other Authors: Kuo-Guan Wu
Format: Others
Language:en_US
Published: 2019
Online Access:http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5441025%22.&searchmode=basic
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spelling ndltd-TW-107NCHU54410252019-11-30T06:09:40Z http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5441025%22.&searchmode=basic On the simplification of multi-focus image fusion using dictionary-based sparse representation 基於稀疏表示分類器與字典學習的快速多焦距影像融合技術 Chien-an Lin 林建安 碩士 國立中興大學 電機工程學系所 107 This paper proposes a fast implementation for multi-focus image fusion using dictionary-based sparse representation. The proposed method reduces the computation complexity of the existing method by synthesizing feature signals from the trained sparse coefficient feature vectors in order to classify each pixel in a source image as focused or defocused, Since the computation of the OMP algorithm for sparse coefficient the exist method complexity of the proposed method can be only 1/100 of [1]. Simulation results further demonstrate that the fused image of the proposed method has the same quality as that of the existing method. Kuo-Guan Wu 吳國光 2019 學位論文 ; thesis 27 en_US
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description 碩士 === 國立中興大學 === 電機工程學系所 === 107 === This paper proposes a fast implementation for multi-focus image fusion using dictionary-based sparse representation. The proposed method reduces the computation complexity of the existing method by synthesizing feature signals from the trained sparse coefficient feature vectors in order to classify each pixel in a source image as focused or defocused, Since the computation of the OMP algorithm for sparse coefficient the exist method complexity of the proposed method can be only 1/100 of [1]. Simulation results further demonstrate that the fused image of the proposed method has the same quality as that of the existing method.
author2 Kuo-Guan Wu
author_facet Kuo-Guan Wu
Chien-an Lin
林建安
author Chien-an Lin
林建安
spellingShingle Chien-an Lin
林建安
On the simplification of multi-focus image fusion using dictionary-based sparse representation
author_sort Chien-an Lin
title On the simplification of multi-focus image fusion using dictionary-based sparse representation
title_short On the simplification of multi-focus image fusion using dictionary-based sparse representation
title_full On the simplification of multi-focus image fusion using dictionary-based sparse representation
title_fullStr On the simplification of multi-focus image fusion using dictionary-based sparse representation
title_full_unstemmed On the simplification of multi-focus image fusion using dictionary-based sparse representation
title_sort on the simplification of multi-focus image fusion using dictionary-based sparse representation
publishDate 2019
url http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5441025%22.&searchmode=basic
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