Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection

Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection

We propose a novel fusion method of IR (infrared) and visual images to combine distinct information from two sources. To decompose an image into its low and high frequency components, we use Gaussian and Laplacian decomposition. The strong high frequency information in the two sources can be easily...

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Bibliographic Details
Main Authors: Seohyung Lee, Daeho Lee
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2016/3130681
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spelling doaj-e2078a2967214dabb1ec0cd8f293960d2020-11-24T22:42:48ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/31306813130681Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge SelectionSeohyung Lee0Daeho Lee1Department of Electronics and Radio Engineering, Kyung Hee University, Yongin 17104, Republic of KoreaHumanitas College, Kyung Hee University, Yongin 17104, Republic of KoreaWe propose a novel fusion method of IR (infrared) and visual images to combine distinct information from two sources. To decompose an image into its low and high frequency components, we use Gaussian and Laplacian decomposition. The strong high frequency information in the two sources can be easily fused by selecting the large magnitude of Laplacian images. The distinct low frequency information, however, is not as easily determined. As such, we use histogram distributions of the two sources. Therefore, experimental results show that the fused images can contain the dominant characteristics of both sources.http://dx.doi.org/10.1155/2016/3130681
collection DOAJ
language English
format Article
sources DOAJ
author Seohyung Lee
Daeho Lee
spellingShingle Seohyung Lee
Daeho Lee
Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection
Mathematical Problems in Engineering
author_facet Seohyung Lee
Daeho Lee
author_sort Seohyung Lee
title Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection
title_short Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection
title_full Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection
title_fullStr Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection
title_full_unstemmed Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection
title_sort fusion of ir and visual images based on gaussian and laplacian decomposition using histogram distributions and edge selection
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2016-01-01
description We propose a novel fusion method of IR (infrared) and visual images to combine distinct information from two sources. To decompose an image into its low and high frequency components, we use Gaussian and Laplacian decomposition. The strong high frequency information in the two sources can be easily fused by selecting the large magnitude of Laplacian images. The distinct low frequency information, however, is not as easily determined. As such, we use histogram distributions of the two sources. Therefore, experimental results show that the fused images can contain the dominant characteristics of both sources.
url http://dx.doi.org/10.1155/2016/3130681
work_keys_str_mv AT seohyunglee fusionofirandvisualimagesbasedongaussianandlaplaciandecompositionusinghistogramdistributionsandedgeselection
AT daeholee fusionofirandvisualimagesbasedongaussianandlaplaciandecompositionusinghistogramdistributionsandedgeselection
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