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Exposure Correction and Local Enhancement for Backlit Image Restoration

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Image and Video Technology (PSIVT 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11854))

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Abstract

Backlighting is a poor illumination condition where the primary light source illuminates a part of the scene from behind. While the part of the scene (often termed as backlit) suffers from low lighting condition, rest of the scene is either well-exposed or over-exposed. We aims to restore such images through enhancement using exposure correction. We generate pseudo images based on the relation of exposure with aperture and shutter speed in a camera. Human visual system (HVS)-sensitive and spatial frequency-aware multi-scale fusion is carried out for exposure correction to produce a globally enhanced image from the input and the pseudo images. Following this, we locally enhance the globally enhanced image to incorporate the information of frequently appearing intensity differences in a spatial neighborhood. Experimental results show that our technique outperforms other relevant approaches subjectively. Quantitative evaluation in terms of DE, EME, PixDist, LOE, AMBE measures shows the superiority of our technique over the other techniques. Our technique is faster than the approaches compared here while generating enhanced and naturalness preserved outputs.

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Authors and Affiliations

  1. Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India

    Sobhan Kanti Dhara & Debashis Sen

Authors
  1. Sobhan Kanti Dhara
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  2. Debashis Sen
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Correspondence to Sobhan Kanti Dhara .

Editor information

Editors and Affiliations

  1. Chonnam National University, Gwangju, Korea (Republic of)

    Chilwoo Lee

  2. Dalian University of Technology, Dalian, China

    Zhixun Su

  3. National Institute of Informatics, Tokyo, Japan

    Akihiro Sugimoto

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Dhara, S.K., Sen, D. (2019). Exposure Correction and Local Enhancement for Backlit Image Restoration. In: Lee, C., Su, Z., Sugimoto, A. (eds) Image and Video Technology. PSIVT 2019. Lecture Notes in Computer Science(), vol 11854. Springer, Cham. https://doi.org/10.1007/978-3-030-34879-3_14

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  • DOI: https://doi.org/10.1007/978-3-030-34879-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34878-6

  • Online ISBN: 978-3-030-34879-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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