Preprint Article Version 1 This version is not peer-reviewed

Adaptive Multi-Scale Entropy Fusion De-hazing based on Fractional Order

Version 1 : Received: 21 July 2018 / Approved: 22 July 2018 / Online: 22 July 2018 (11:30:40 CEST)

A peer-reviewed article of this Preprint also exists.

Nnolim, U.A. Adaptive Multi-Scale Entropy Fusion De-Hazing Based on Fractional Order. J. Imaging 2018, 4, 108. Nnolim, U.A. Adaptive Multi-Scale Entropy Fusion De-Hazing Based on Fractional Order. J. Imaging 2018, 4, 108.

Journal reference: J. Imaging 2018, 4, 108
DOI: 10.3390/jimaging4090108

Abstract

This paper describes a proposed fractional filter-based multi-scale underwater and hazy image enhancement algorithm. The proposed system combines a modified global contrast operator with fractional order-based multi-scale filters used to generate several images, which are fused based on entropy and standard deviation. The multi-scale-global enhancement technique enables fully adaptive and controlled colour correction and contrast enhancement without over exposure of highlights when processing hazy and underwater images. This in addition to illumination/reflectance estimation coupled with global and local contrast enhancement. The proposed algorithm is also compared with the most recent available state-of-the-art multi-scale fusion de-hazing algorithm. Experimental comparisons indicate that the proposed approach yields better edge and contrast enhancement results without halo effect, colour degradation and is faster and more adaptive than all other algorithms from the literature.

Subject Areas

fractional order calculus-based multi-scale contrast operator; hybrid local-global contrast enhancement; underwater image enhancement processing; hazy image contrast enhancement; entropy guided fusion

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