Abstract
The proposed work introduces a novel Bacterial Foraging (BF)-Fuzzy synergism based dehazing method to enhance the visibility of degraded hazy images. The proposed method performs contrast enhancement, edge & noise detection, noise removal and edge-sharpening (all the four important aspects of dehazing). In the first step of the method, each pixel of the degraded V channel of hazy image is enhanced using unique defuzzified mapping constant which is evaluated depending upon its Haze-concentration and Log-sigmoid transformation function values to prevent poor or over-enhancement. Subsequently, in the next step simultaneous edge & noise detection is performed using BF algorithm in combination with one set of novel FI rules. These rules beside performing simultaneous edge & noise detection also evaluate edge-strengths of all possible edge directions. BF algorithm is used here to determine the most suitable direction for the movement of bacteria within each image patch. It also facilities the selection of true edge pixels by imposing constraints on defuzzified edge-strengths which eliminates any chances of false edge detection. Noisy pixels are filtered here according to their extent of corruption w.r.t each pixel located within their neighbourhood using another novel set of FI rules to prevent undesired edge-blurring. Finally, selected edges are sharpened using unique sharpening factors which are evaluated according to their respective edge-strength using a set of novel FI rules to prevent the occurrence of undesirable halo-artifacts in outputs. Comparative qualitative, quantitative and run-time complexity analyses’ results also proved the excellence of the proposed work over several state-of-the art methods.
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Banerjee, S., Sinha Chaudhuri, S. Bacterial Foraging-Fuzzy synergism based Image Dehazing. Multimed Tools Appl 80, 8377–8421 (2021). https://doi.org/10.1007/s11042-020-09794-6
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DOI: https://doi.org/10.1007/s11042-020-09794-6