Correcting Low-Illumination Images Using Multi-Scale Fusion in a Pyramidal Framework

Das, Swadhin Sambit; Roy, Manali; Mukhopadhyay, Susanta

doi:10.1109/wispnet48689.2020.9198536

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2020

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“…Several previous studies have used this method for image enhancement [11], [13]- [16], and video enhancement [17], [18] with several additional filters and other algorithms. The MSR method can also improve color in images [19]- [23], low illumination [24], [25], etcetera.…”

Section: Methodsmentioning

confidence: 99%

Multiscale Retinex Application to Analyze Face Recognition

Supriyanto

Harika

Ramadiani

et al. 2020

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The main challenge that facial recognition introduces is the difficulty of uneven lighting or dark tendencies. The image is poorly lit, which makes it difficult for the system to perform facial recognition. This study aims to normalize the lighting in the image using the Multiscale Retinex method. This method is applied to a face recognition system based on Principal Component Analysis to determine whether this method effectively improves images with uneven lighting. The results showed that the Multiscale Retinex approach to face recognition's correctness was better, from 40% to 76%. Multiscale Retinex has the advantage of dark facial image types because it produces a brighter image output.

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