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Interactive Fusion for Multi-exposure Images

Published: 09 April 2021 Publication History

Abstract

Exposure fusion methods are effective for directly fusing multi-exposure images to one high-quality image. Most exposure fusion methods can generate a more natural and visually pleasing image than tone-mapping methods, but they do not preserve so much fine details as tone-mapping methods, especially in the brightest and darkest regions. In this paper, a more flexibility exposure fusion method is proposed so that users can manipulate details according to their preference. Our method extracts different amount of details only from the most underexposed image and the most overexposed image by using local Laplacian filtering before multi-resolution weighted blending. Compared with previous methods, our interactive detail-variable method is much more flexible and effective on detail-preserving in the brightest and darkest regions.

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ICIT '20: Proceedings of the 2020 8th International Conference on Information Technology: IoT and Smart City
December 2020
266 pages
ISBN:9781450388559
DOI:10.1145/3446999
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2021

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Author Tags

  1. HDR
  2. Laplacian pyramid
  3. exposure fusion
  4. image enhancement
  5. tone mapping

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ICIT 2020
ICIT 2020: IoT and Smart City
December 25 - 27, 2020
Xi'an, China

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