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Modified differential evolution algorithm for contrast and brightness enhancement of satellite images
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“The main advantage of Radial Basis Function Neural Network (RBFNN) is its immunity to noise signals; perhaps due to its large number of tunable parameters [142].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [142]
Citations
Cites
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Cited by
Applications and Challenges of Artificial Intelligence in Space Missions
Oche, P. A., Ewa, G. A., & Ibekwe, N. (2024) · IEEE Access · doi:10.1109/access.2021.3132500 · Cited by 68
“In [140] Suresh et al. proposed a new method—Modified Differential Evolution (MDE) algorithm for contrast and brightness enhancement.”
Method
Metadata
- Authors
- Suresh, S., & Lal, S.
- Affiliations
- National Institute of Technology Karnataka (IN)
- Corresponding author
- Lal, Shyam
- Venue
- Applied Soft Computing
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 61
- Pages
- 622-641
- ISSN
- 1568-4946 (ISSN-L)
- OpenAlex
- W2750002240
- Cited by
- 73
- References
- 1
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 9 · 2023: 7 · 2022: 10 · 2021: 6 · 2020: 10 · 2019: 14 · 2018: 11
- FWCI
- 3.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Applied Soft Computing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Satellite Image Processing and Photogrammetry
- Keywords
- satellite image enhancement, contrast stretching, brightness enhancement, modified differential evolution, cuckoo search algorithm, hybrid metaheuristic, edge preservation
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