Open Access
Issue |
JNWPU
Volume 43, Number 1, February 2025
|
|
---|---|---|
Page(s) | 140 - 148 | |
DOI | https://doi.org/10.1051/jnwpu/20254310140 | |
Published online | 18 April 2025 |
- SOUNDRAPANDIYAN R, SATAPATHY S C, et al. A comprehensive survey on image enhancement techniques with special emphasis on infrared images[J]. Multimedia Tools and Applications, 2022, 81(7): 9045–9077. [Article] [Google Scholar]
- JÄHNE B. Digital image processing[M]. Cham: Springer Science&Business Media, 2005 [Google Scholar]
- SONG Yanfeng, SHAO Xiaopeng, XU Jun. New enhancement algorithm for infrared image based on double plateaus histogram[J]. Infrared and Laser Engineering, 2008(2): 308–311. [Article] (in Chinese) [Google Scholar]
- LIANG K, MA Y, XIE Y, et al. A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization[J]. Infrared Physics&Technology, 2012, 55(4): 309–315 [Google Scholar]
- LIM S H, MAT ISA N A, OOI C H, et al. A new histogram equalization method for digital image enhancement and brightness preservation[J]. Signal, Image and Video Processing, 2015, 9(3): 675–689. [Article] [Google Scholar]
- LEE S, KIM D, KIM C. Slope-based histogram equalization for real-time display of high-quality infrared imagery[C]//2018 IEEE International Conference on Consumer Electronics, 2018: 206–212 [Google Scholar]
- ZARIE M, PARSAYAN A, HAJGHASSEM H. Image contrast enhancement using triple clipped dynamic histogram equalisation based on standard deviation[J]. IET Image Processing, 2019, 13(7): 1081–1089. [Article] [Google Scholar]
- LEE S, KIM D, KIM C. Ramp distribution-based image enhancement techniques for infrared images[J]. IEEE Signal Process-ing Letters, 2018, 25(7): 931–935. [Article] [Google Scholar]
- LI S, JIN W, LI L, et al. An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization[J]. Infrared Physics&Technology, 2018, 90: 164–174 [Google Scholar]
- ZHANG H, QIAN W, WAN M, et al. Infrared image enhancement algorithm using local entropy mapping histogram adaptive segmentation[J]. Infrared Physics&Technology, 2022, 120: 104000 [Google Scholar]
- JONES G, WILLETT P, GLEN R C, et al. Development and validation of a genetic algorithm for flexible docking[J]. Journal of Molecular Biology, 1997, 267(3): 727–748. [Article] [Google Scholar]
- BHANDARI A K, KANDHWAY P, MAURYA S. Salp swarm algorithm-based optimally weighted histogram framework for image enhancement[J]. IEEE Trans on Instrumentation and Measurement, 2020, 69(9): 6807–6815. [Article] [Google Scholar]
- MIRJALILI S, GANDOMI A H, MIRJALILI S Z, et al. Salp swarm algorithm: a bio-inspired optimizer for engineering design problems[J]. Advances in Engineering Software, 2017, 114: 163–191. [Article] [Google Scholar]
- HUANG J, MA Y, ZHANG Y, et al. Infrared image enhancement algorithm based on adaptive histogram segmentation[J]. Applied Optics, 2017, 56(35): 9686. [Article] [Google Scholar]
- ZUO C, CHEN Q, LIU N, et al. Display and detail enhancement for high-dynamic-range infrared images[J]. Optical Engineering, 2011, 50(12): 1 [Google Scholar]
- LIU N, ZHAO D. Detail enhancement for high-dynamic-range infrared images based on guided image filter[J]. Infrared Physics&Technology, 2014, 67: 138–147 [Google Scholar]
- LI Y, LIU N, XU J, et al. Detail enhancement of infrared image based on bi-exponential edge preserving smoother[J]. Optik, 2019, 199: 163300. [Article] [Google Scholar]
- FENG X, PAN Z. Detail enhancement for infrared images based on relativity of Gaussian-adaptive bilateral filter[J]. OSA Continuum, 2021, 4(10): 2671. [Article] [Google Scholar]
- CHEN Y, KANG J U, ZHANG G, et al. Real-time infrared image detail enhancement based on fast guided image filter and plateau equalization[J]. Applied Optics, 2020, 59(21): 6407. [Article] [Google Scholar]
- LYU H, SHAN P, SHI H, et al. An adaptive bilateral filtering method based on improved convolution kernel used for infrared image enhancement[J]. Signal, Image and Video Processing, 2022, 16(8): 2231–2237 [Google Scholar]
- WU Xiaolin. A linear programming approach for optimal contrast-tone mapping[J]. IEEE Trans on Image Processing, 2011, 20(5): 1262–1272 [Google Scholar]
- MORRIS N J W, AVIDAN S, MATUSIK W, et al. Statistics of infrared images[C]//2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007: 1–7 [Google Scholar]
- BERG A, AHLBERG J, FELSBERG M. A thermal object tracking benchmark[C]//2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2015: 1–6 [Google Scholar]
- WU Z, FULLER N, THERIAULT D, et al. A thermal infrared video benchmark for visual analysis[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2014: 201–208 [Google Scholar]
- SHANNON C E. A mathematical theory of communication[J]. The Bell System Technical Journal, 1948, 27(3): 379–423. [Article] [CrossRef] [Google Scholar]
- LAI R, YANG Y, WANG B, et al. A quantitative measure based infrared image enhancement algorithm using plateau histogram[J]. Optics Communications, 2010, 283(21): 4283–4288 [Google Scholar]
- MITTAL A, SOUNDARARAJAN R, BOVIK A C. Making a "completely blind" image quality analyzer[J]. IEEE Signal Processing Letters, 2013, 20(3): 209–212 [NASA ADS] [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.