Cuckoo search-based modified bi-histogram equalisation method to enhance the cancerous tissues in mammography images

Adaptive Entropy Index Histogram Equalization for Poor Contrast Images

“…Given these features, NIOAs are efficient and powerful algorithms for solving problems in the image processing field, such as image enhancement, image segmentation, classification, and clustering. Several NIOAs have been hybridized with HE in the field of image enhancement to improve image contrast and preserve brightness such as [60], [21], [61], [62], [63], [64], [65], [66], and [67]. For instance, the authors in [60] hybridized PSO with CLAHE to enhance mammogram images.…”

“…Meanwhile, the authors in [21] optimized the parameterized bi-thresholded HE by computing the entropy value in real-coded GA for brain magnetic resonance images (MRI). The authors in [61] hybridized the cuckoo search algorithm particle with OBBWTHE to obtain a quality index based on local variance and fractal dimension as multi-objective functions for mammogram images. The authors in [62] hybridized the ABC algorithm with MTHE to maximize entropy as the fitness function for histopathology images.…”

Local search-based dynamically adapted bat algorithm in image enhancement domain

“…Here another parameterised variant of HE has been considered as an enhancement method in EM 4 Dhal et al, 2017b).…”

“…Enhancement method is same as the method described in EM 5 Dhal et al, 2017b). Kapur's entropy-based Dhal et al, 2017b) method has been used to segment the input histogram.…”

“…In this study, image enhancement techniques (Gonzalez and Woods, 2002) have been formulated as optimisation problems and solved by nature inspired optimisation algorithms. Genetic algorithm (GA), particle swarm optimisation (PSO), differential evolution (DE), Cuckoo search (CS), artificial bee colony (ABC), firefly algorithm (FA) are some nature inspired metaheuristic algorithms which were effectively used in image enhancement field Ghosh, 2009, 2011;Munteanu and Rosa, 2001;Pal et al, 1994;Hashemi et al, 2010;Coelho et al, 2009;Dhal et al, 2015aDhal et al, , 2015bDhal et al, , 2015cDhal et al, , 2015dDhal et al, , 2017bDhal et al, , 2017aShanmugavadivu et al, 2014;Braik et al, 2007;Quraishi et al, 2012;Das, 2016, 2015;Quraishi et al, 2013). PSO gave better results than GA in the image enhancement domain by maximising employed entropy-based objective function.…”