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Nonlinear Enhancement of Extremely High Contrast Images for Visibility Improvement

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Computer Vision, Graphics and Image Processing

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4338))

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.

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© 2006 Springer-Verlag Berlin Heidelberg

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Asari, K.V., Oguslu, E., Arigela, S. (2006). Nonlinear Enhancement of Extremely High Contrast Images for Visibility Improvement. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_22

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  • DOI: https://doi.org/10.1007/11949619_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68301-8

  • Online ISBN: 978-3-540-68302-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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