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題名 Two-Exposure Image Fusion Based on Optimized Adaptive Gamma Correction
作者 彭彥璁
Peng, Yan-Tsung
Liao, He-Hao;Chen, Ching-Fu
貢獻者 資科系
關鍵詞 two-exposure image fusion; gamma correction; high dynamic imaging
日期 2021-12
上傳時間 6-Feb-2023 14:30:36 (UTC+8)
摘要 In contrast to conventional digital images, high-dynamic-range (HDR) images have a broader range of intensity between the darkest and brightest regions to capture more details in a scene. Such images are produced by fusing images with different exposure values (EVs) for the same scene. Most existing multi-scale exposure fusion (MEF) algorithms assume that the input images are multi-exposed with small EV intervals. However, thanks to emerging spatially multiplexed exposure technology that can capture an image pair of short and long exposure simultaneously, it is essential to deal with two-exposure image fusion. To bring out more well-exposed contents, we generate a more helpful intermediate virtual image for fusion using the proposed Optimized Adaptive Gamma Correction (OAGC) to have better contrast, saturation, and well-exposedness. Fusing the input images with the enhanced virtual image works well even though both inputs are underexposed or overexposed, which other state-of-the-art fusion methods could not handle. The experimental results show that our method performs favorably against other state-of-the-art image fusion methods in generating high-quality fusion results.
關聯 Sensors, Vol.22, No.1, 24
資料類型 article
DOI https://doi.org/10.3390/s22010024
dc.contributor 資科系
dc.creator (作者) 彭彥璁
dc.creator (作者) Peng, Yan-Tsung
dc.creator (作者) Liao, He-Hao;Chen, Ching-Fu
dc.date (日期) 2021-12
dc.date.accessioned 6-Feb-2023 14:30:36 (UTC+8)-
dc.date.available 6-Feb-2023 14:30:36 (UTC+8)-
dc.date.issued (上傳時間) 6-Feb-2023 14:30:36 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/143302-
dc.description.abstract (摘要) In contrast to conventional digital images, high-dynamic-range (HDR) images have a broader range of intensity between the darkest and brightest regions to capture more details in a scene. Such images are produced by fusing images with different exposure values (EVs) for the same scene. Most existing multi-scale exposure fusion (MEF) algorithms assume that the input images are multi-exposed with small EV intervals. However, thanks to emerging spatially multiplexed exposure technology that can capture an image pair of short and long exposure simultaneously, it is essential to deal with two-exposure image fusion. To bring out more well-exposed contents, we generate a more helpful intermediate virtual image for fusion using the proposed Optimized Adaptive Gamma Correction (OAGC) to have better contrast, saturation, and well-exposedness. Fusing the input images with the enhanced virtual image works well even though both inputs are underexposed or overexposed, which other state-of-the-art fusion methods could not handle. The experimental results show that our method performs favorably against other state-of-the-art image fusion methods in generating high-quality fusion results.
dc.format.extent 97 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Sensors, Vol.22, No.1, 24
dc.subject (關鍵詞) two-exposure image fusion; gamma correction; high dynamic imaging
dc.title (題名) Two-Exposure Image Fusion Based on Optimized Adaptive Gamma Correction
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.3390/s22010024
dc.doi.uri (DOI) https://doi.org/10.3390/s22010024