Article

Image fusion for context enhancement and video surrealism

Authors:

Jingyi YuAuthors Info & Claims

NPAR '04: Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering

Pages 85 - 152

https://doi.org/10.1145/987657.987671

Published: 07 June 2004 Publication History

Abstract

We present a class of image fusion techniques to automatically combine images of a scene captured under different illumination. Beyond providing digital tools for artists for creating surrealist images and videos, the methods can also be used for practical applications. For example, the non-realistic appearance can be used to enhance the context of nighttime traffic videos so that they are easier to understand. The context is automatically captured from a fixed camera and inserted from a day-time image (of the same scene). Our approach is based on a gradient domain technique that preserves important local perceptual cues while avoiding traditional problems such as aliasing, ghosting and haloing. We presents several results in generating surrealistic videos and in increasing the information density of low quality nighttime videos.

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Image fusion for context enhancement and video surrealism
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
  2. Computer graphics

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Published In

cover image ACM Conferences

NPAR '04: Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering

June 2004

150 pages

ISBN:1581138873

DOI:10.1145/987657

Conference Chairs:
Aaron Hertzmann
University of Toronto, Canada
,
Craig Kaplan
University of Waterloo, Canada
,
Editor:
Stephen N. Spencer
The University of Washington

Copyright © 2004 ACM.

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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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Annecy Animation Festival

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Association for Computing Machinery

New York, NY, United States

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Published: 07 June 2004

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NPAR04: The 3rd International Symposium on Non-Photorealistic Animation

June 7 - 9, 2004

Annecy, France

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Singh PBhandari A(2025)A Review on Computational Low-Light Image Enhancement Models: Challenges, Benchmarks, and PerspectivesArchives of Computational Methods in Engineering10.1007/s11831-025-10226-7Online publication date: 10-Feb-2025
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Zhang YYuan JYan C(2024)Enhanced Seamless Video Fusion: A Convolutional Pyramid-Based 3D Integration AlgorithmSensors10.3390/s2406185224:6(1852)Online publication date: 14-Mar-2024
https://doi.org/10.3390/s24061852
Agarwala ADontcheva MAgrawala MDrucker SColburn ACurless BSalesin DCohen M(2023)Interactive Digital PhotomontageSeminal Graphics Papers: Pushing the Boundaries, Volume 210.1145/3596711.3596775(599-607)Online publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1145/3596711.3596775
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Saad NDahalan ASaudi A(2022)Modified Poisson compositing technique on skewed gridAIMS Mathematics10.3934/math.20221247:2(2176-2194)Online publication date: 2022
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