Texture Smoothing Quality Assessment via Information Entropy
Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. C...
Ausführliche Beschreibung
Autor*in: |
Chong Liu [verfasserIn] Cui Yang [verfasserIn] Mingqiang Wei [verfasserIn] Jun Wang [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Übergeordnetes Werk: |
In: IEEE Access - IEEE, 2014, 8(2020), Seite 88410-88421 |
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Übergeordnetes Werk: |
volume:8 ; year:2020 ; pages:88410-88421 |
Links: |
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DOI / URN: |
10.1109/ACCESS.2020.2993146 |
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Katalog-ID: |
DOAJ054402719 |
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10.1109/ACCESS.2020.2993146 doi (DE-627)DOAJ054402719 (DE-599)DOAJb8e448c7970f41c29b30f72a8283842e DE-627 ger DE-627 rakwb eng TK1-9971 Chong Liu verfasserin aut Texture Smoothing Quality Assessment via Information Entropy 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. Texture filtering IQA smoothness structure similarity entropy Electrical engineering. Electronics. Nuclear engineering Cui Yang verfasserin aut Mingqiang Wei verfasserin aut Jun Wang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 88410-88421 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:88410-88421 https://doi.org/10.1109/ACCESS.2020.2993146 kostenfrei https://doaj.org/article/b8e448c7970f41c29b30f72a8283842e kostenfrei https://ieeexplore.ieee.org/document/9089017/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 88410-88421 |
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10.1109/ACCESS.2020.2993146 doi (DE-627)DOAJ054402719 (DE-599)DOAJb8e448c7970f41c29b30f72a8283842e DE-627 ger DE-627 rakwb eng TK1-9971 Chong Liu verfasserin aut Texture Smoothing Quality Assessment via Information Entropy 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. Texture filtering IQA smoothness structure similarity entropy Electrical engineering. Electronics. Nuclear engineering Cui Yang verfasserin aut Mingqiang Wei verfasserin aut Jun Wang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 88410-88421 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:88410-88421 https://doi.org/10.1109/ACCESS.2020.2993146 kostenfrei https://doaj.org/article/b8e448c7970f41c29b30f72a8283842e kostenfrei https://ieeexplore.ieee.org/document/9089017/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 88410-88421 |
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10.1109/ACCESS.2020.2993146 doi (DE-627)DOAJ054402719 (DE-599)DOAJb8e448c7970f41c29b30f72a8283842e DE-627 ger DE-627 rakwb eng TK1-9971 Chong Liu verfasserin aut Texture Smoothing Quality Assessment via Information Entropy 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. Texture filtering IQA smoothness structure similarity entropy Electrical engineering. Electronics. Nuclear engineering Cui Yang verfasserin aut Mingqiang Wei verfasserin aut Jun Wang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 88410-88421 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:88410-88421 https://doi.org/10.1109/ACCESS.2020.2993146 kostenfrei https://doaj.org/article/b8e448c7970f41c29b30f72a8283842e kostenfrei https://ieeexplore.ieee.org/document/9089017/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 88410-88421 |
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10.1109/ACCESS.2020.2993146 doi (DE-627)DOAJ054402719 (DE-599)DOAJb8e448c7970f41c29b30f72a8283842e DE-627 ger DE-627 rakwb eng TK1-9971 Chong Liu verfasserin aut Texture Smoothing Quality Assessment via Information Entropy 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. Texture filtering IQA smoothness structure similarity entropy Electrical engineering. Electronics. Nuclear engineering Cui Yang verfasserin aut Mingqiang Wei verfasserin aut Jun Wang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 88410-88421 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:88410-88421 https://doi.org/10.1109/ACCESS.2020.2993146 kostenfrei https://doaj.org/article/b8e448c7970f41c29b30f72a8283842e kostenfrei https://ieeexplore.ieee.org/document/9089017/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 88410-88421 |
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Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. |
abstractGer |
Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. |
abstract_unstemmed |
Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available. |
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Texture Smoothing Quality Assessment via Information Entropy |
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|
score |
7.3985844 |