Nonlinear enhancement of extremely high contrast images for visibility improvement

Authors:
K. Vijayan Asari;Ender Oguslu;Saibabu Arigela
Affiliations:
Computational Intelligence and Machine Vision Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, Virginia;Computational Intelligence and Machine Vision Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, Virginia;Computational Intelligence and Machine Vision Laboratory, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, Virginia
Venue:
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Year:
2006

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Abstract

This paper presents a novel image enhancement algorithm using a multilevel windowed inverse sigmoid (MWIS) function for rendering images captured under extremely non uniform lighting conditions. MWIS based image enhancement is a combination of three processes viz. adaptive intensity enhancement, contrast enhancement and color restoration. Adaptive intensity enhancement uses the non linear transfer function to pull up the intensity of underexposed pixels and to pull down the intensity of overexposed pixels of the input image. Contrast enhancement tunes the intensity of each pixel's magnitude with respect to its surrounding pixels. A color restoration process based on relationship between spectral bands and the luminance of the original image is applied to convert the enhanced intensity image back to a color image.