Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2024.2404365
Contrast enhancement of digital images using dragonfly algorithm
Soumyajit Saha
; Department of Computer Science & Engineering, Future Institute of Engineering & Management, Kolkata, West Bengal, India
Somnath Chatterjee
; Department of Computer Science & Engineering, Future Institute of Engineering & Management, Kolkata, West Bengal, India
Shibaprasad Sen
; Department of Computer Science & Engineering, MCKV Institute of Engineering, Howrah, West Bengal, India
Diego Oliva
; Depto. de Ingeniería Electro-Fotónica, Universidad de Guadalajara, CUCEI, Guadalajara, Mexico
*
Marco Perez-Cisneros
; Depto. de Ingeniería Electro-Fotónica, Universidad de Guadalajara, CUCEI, Guadalajara, Mexico
Ram Sarkar
; Department of Computer Science & Engineering, Jadavpur University, Kolkata, West Bengal, India
* Dopisni autor.
Sažetak
Contrast enhancement aims to amplify the visual quality of images by modifying the contrast
level because digital images may get distorted by casual acquisition. The article deals with contrast enhancement as an optimization problem and uses the Dragonfly Algorithm (DA) to find the
optimal grey-level intensity values. The DA for contrast enhancement uses five control parameters (entropy, number of edges, total intensities of edges, the variance of the probability of
occurrence of each grey value, and the number of grey levels) to generate an objective function. An ablation study is also performed to understand how different controlling parameter
combinations contribute to determining the optimal solution. The proposed approach considers
24 grey-scale images from the Kodak dataset and metrics as Peak Signal-to-Noise Ratio (PSNR),
Visual Information Fidelity (VIF), and Structural Similarity Index Measure (SSIM) to verify the output’s performance. The PSNR, VIF, and SSIM values in the experiments are 30.87, 0.7451, and
0.9523, respectively. The experimental observations reveal that the proposed DA-based image
contrast enhancement produces high-quality images from its low-contrast counterparts. Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this Github repository
Ključne riječi
Dragonfly algorithm; image contrast enhancement; Kodak dataset; meta-heuristic
Hrčak ID:
326345
URI
Datum izdavanja:
23.9.2024.
Posjeta: 0 *