An adaptive two-scale biomedical image fusion method with statistical comparisons

Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Du, Jiao [verfasserIn] Fang, Meie [verfasserIn] Yu, Yufeng [verfasserIn] Lu, Gang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Base and detail Friedman test Otsu's method Adaptive two-scale representation Statistical significant analysis

Übergeordnetes Werk:	Enthalten in: Computer methods and programs in biomedicine - Amsterdam : Elsevier, 1985, 196
Übergeordnetes Werk:	volume:196

DOI / URN:	10.1016/j.cmpb.2020.105603

Katalog-ID:	ELV004845528

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520			\|a Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data.
650		4	\|a Base and detail
650		4	\|a Friedman test
650		4	\|a Otsu's method
650		4	\|a Adaptive two-scale representation
650		4	\|a Statistical significant analysis
700	1		\|a Fang, Meie \|e verfasserin \|4 aut
700	1		\|a Yu, Yufeng \|e verfasserin \|4 aut
700	1		\|a Lu, Gang \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Computer methods and programs in biomedicine \|d Amsterdam : Elsevier, 1985 \|g 196 \|h Online-Ressource \|w (DE-627)265783593 \|w (DE-600)1466281-4 \|w (DE-576)074890883 \|x 1872-7565 \|7 nnns
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936	b	k	\|a 44.32 \|j Medizinische Mathematik \|j medizinische Statistik
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Indexfelder

author_variant	j d jd m f mf y y yy g l gl
matchkey_str	article:18727565:2020----::ndpiewsaeimdclmgfsomtowts
hierarchy_sort_str	2020
bklnumber	44.32
publishDate	2020
allfields	10.1016/j.cmpb.2020.105603 doi (DE-627)ELV004845528 (ELSEVIER)S0169-2607(20)31436-X DE-627 ger DE-627 rda eng 004 610 DE-600 44.32 bkl Du, Jiao verfasserin aut An adaptive two-scale biomedical image fusion method with statistical comparisons 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data. Base and detail Friedman test Otsu's method Adaptive two-scale representation Statistical significant analysis Fang, Meie verfasserin aut Yu, Yufeng verfasserin aut Lu, Gang verfasserin aut Enthalten in Computer methods and programs in biomedicine Amsterdam : Elsevier, 1985 196 Online-Ressource (DE-627)265783593 (DE-600)1466281-4 (DE-576)074890883 1872-7565 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.32 Medizinische Mathematik medizinische Statistik AR 196
spelling	10.1016/j.cmpb.2020.105603 doi (DE-627)ELV004845528 (ELSEVIER)S0169-2607(20)31436-X DE-627 ger DE-627 rda eng 004 610 DE-600 44.32 bkl Du, Jiao verfasserin aut An adaptive two-scale biomedical image fusion method with statistical comparisons 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data. Base and detail Friedman test Otsu's method Adaptive two-scale representation Statistical significant analysis Fang, Meie verfasserin aut Yu, Yufeng verfasserin aut Lu, Gang verfasserin aut Enthalten in Computer methods and programs in biomedicine Amsterdam : Elsevier, 1985 196 Online-Ressource (DE-627)265783593 (DE-600)1466281-4 (DE-576)074890883 1872-7565 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.32 Medizinische Mathematik medizinische Statistik AR 196
allfields_unstemmed	10.1016/j.cmpb.2020.105603 doi (DE-627)ELV004845528 (ELSEVIER)S0169-2607(20)31436-X DE-627 ger DE-627 rda eng 004 610 DE-600 44.32 bkl Du, Jiao verfasserin aut An adaptive two-scale biomedical image fusion method with statistical comparisons 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data. Base and detail Friedman test Otsu's method Adaptive two-scale representation Statistical significant analysis Fang, Meie verfasserin aut Yu, Yufeng verfasserin aut Lu, Gang verfasserin aut Enthalten in Computer methods and programs in biomedicine Amsterdam : Elsevier, 1985 196 Online-Ressource (DE-627)265783593 (DE-600)1466281-4 (DE-576)074890883 1872-7565 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.32 Medizinische Mathematik medizinische Statistik AR 196
allfieldsGer	10.1016/j.cmpb.2020.105603 doi (DE-627)ELV004845528 (ELSEVIER)S0169-2607(20)31436-X DE-627 ger DE-627 rda eng 004 610 DE-600 44.32 bkl Du, Jiao verfasserin aut An adaptive two-scale biomedical image fusion method with statistical comparisons 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data. Base and detail Friedman test Otsu's method Adaptive two-scale representation Statistical significant analysis Fang, Meie verfasserin aut Yu, Yufeng verfasserin aut Lu, Gang verfasserin aut Enthalten in Computer methods and programs in biomedicine Amsterdam : Elsevier, 1985 196 Online-Ressource (DE-627)265783593 (DE-600)1466281-4 (DE-576)074890883 1872-7565 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.32 Medizinische Mathematik medizinische Statistik AR 196
allfieldsSound	10.1016/j.cmpb.2020.105603 doi (DE-627)ELV004845528 (ELSEVIER)S0169-2607(20)31436-X DE-627 ger DE-627 rda eng 004 610 DE-600 44.32 bkl Du, Jiao verfasserin aut An adaptive two-scale biomedical image fusion method with statistical comparisons 2020 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data. Base and detail Friedman test Otsu's method Adaptive two-scale representation Statistical significant analysis Fang, Meie verfasserin aut Yu, Yufeng verfasserin aut Lu, Gang verfasserin aut Enthalten in Computer methods and programs in biomedicine Amsterdam : Elsevier, 1985 196 Online-Ressource (DE-627)265783593 (DE-600)1466281-4 (DE-576)074890883 1872-7565 nnns volume:196 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 44.32 Medizinische Mathematik medizinische Statistik AR 196
language	English
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author	Du, Jiao
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title_sort	an adaptive two-scale biomedical image fusion method with statistical comparisons
title_auth	An adaptive two-scale biomedical image fusion method with statistical comparisons
abstract	Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data.
abstractGer	Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data.
abstract_unstemmed	Two-scale image representation of base and detail in the spatial-domain is a well-known decomposition scheme for its lower computational complexity than that performed in the transform-domain in the field of image fusion. Unfortunately, for a pseudo-colour input image, the base and detail images in the spatial-domain obtained via image decomposition scheme always display in greyscale. In this paper, a two-scale image fusion method with adaptive threshold obtained by Otsu's method is proposed for pseudo-colour image in the colour space domain. For greyscale image, detail and base image are obtained using structural information extracted from the difference image between a global and a local patch size. Consequently, local edge-preserving filter for preserving luminance information and local energy with the discussed window size are adopted to combine base and detail image. Experimental results show that structural and luminance information has been better preserved in terms of subjective and objective evaluations for medical image and protein image fusion. Specially, a two-step non-parametric statistical test (Friedman test and Nemenyi post-hoc test) with p-values is adopted to analysis the statistical significant of the relative difference between the proposed and compared methods in terms of values of objective metrics including 30 co-registered pairs of imaging data.
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title_short	An adaptive two-scale biomedical image fusion method with statistical comparisons
remote_bool	true
author2	Fang, Meie Yu, Yufeng Lu, Gang
author2Str	Fang, Meie Yu, Yufeng Lu, Gang
ppnlink	265783593
mediatype_str_mv	c
isOA_txt	false
hochschulschrift_bool	false
doi_str	10.1016/j.cmpb.2020.105603
up_date	2024-07-07T00:20:27.679Z
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An adaptive two-scale biomedical image fusion method with statistical comparisons

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