Fitness based weighted flower pollination algorithm with mutation strategies for image enhancement

A Hybrid Swarming Algorithm for Adaptive Enhancement of Low-Illumination Images

“…For example, [33] used particle swarm optimization to optimize the histogram equalization of gamma correction, effectively avoiding excessive enhancement and unnatural artifacts. Inspired by this research, an increasing number of swarm intelligence algorithms are being applied to image enhancement, such as FPA [34] and the Selfish Herd Optimizer (SHO) [35]. Yan et al [36] enhanced images of autonomous underwater vehicles using the whale algorithm.…”

“…Methods Benefits and Shortcomings [25] three-part histogram equalization effectively enhanced images; artifacts, sawtooth effects, and over-enhancement [26] triple-clipping dynamic histogram equalization the performance has room for improvement [27] divided the quantiles of the histogram overcame the mean shift problem and enhanced contrast; excessive noise amplification [28] enhanced retinal fundus images avoided excessive noise amplification; results may not be ideal for details [29] CLAHE, Gauss mask algorithm, and differential processing removed noise and retained edge information while improving contrast; the noise point of the weld image has not been effectively improved [30] a cross-correlation color histogram translation algorithm resolved red artifacts in dust images and reduced color distortion [31] a blind inverse gamma correction algorithm can be seamlessly extended to a masked image and multi-channel image, and is free of the arbitrary tuning parameter [32] a simple and efficient method based on the membership function and gamma correction overcame over-and under-enhancement issues [33] used particle swarm optimization to optimize the histogram equalization of gamma correction avoided excessive enhancement and unnatural artifacts [34] used FPA to optimize the histogram equalization of gamma correction produceed more robust, scalable, and precise results than the original FPA [35] used SHO to optimize the histogram equalization of gamma correction two different solutions [36] used the whale algorithm enhanced images of autonomous underwater vehicles [37] used the parameters of the multi-objective Grasshopper algorithm (GOA), the Duffing oscillator model, and thhe homomorphic filter effectively avoided image color distortion and excessive noise [38] the artificial bee colony algorithm with weights emphasized details and reduced noise…”