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Related Experiment Video

Updated: May 11, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Single image dehazing by multi-scale fusion.

Codruta Orniana Ancuti¹, Cosmin Ancuti

¹Expertise Center for Digital Media, Hasselt University, Diepenbeek 3590, Belgium. codruta.ancuti@uhasselt.be

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|May 16, 2013

Summary

This summary is machine-generated.

This study presents a new single-image method to improve visibility in hazy outdoor scenes. The fusion-based technique effectively enhances degraded images for clearer outdoor viewing.

Related Experiment Videos

Last Updated: May 11, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Area of Science:

Computer Vision
Image Processing
Atmospheric Optics

Background:

Haze significantly degrades outdoor scene visibility due to atmospheric particles scattering and absorbing light.
Existing dehazing methods often require multiple images or complex algorithms.

Purpose of the Study:

To introduce a novel single-image approach for enhancing visibility in hazy scenes.
To develop an effective fusion-based strategy for image dehazing.

Main Methods:

A fusion-based strategy using two derived hazy image inputs with white balance and contrast enhancement.
Weight maps (luminance, chromaticity, saliency) filter important features for effective blending.
A multiscale approach using Laplacian pyramid representation minimizes artifacts.

Main Results:

The method successfully enhances visibility in single degraded images.
Fusion of derived inputs preserves regions with good visibility.
Per-pixel processing ensures straightforward implementation.

Conclusions:

The novel fusion-based technique is effective for single-image dehazing.
The method achieves results comparable to or better than complex state-of-the-art techniques.
The approach is suitable for real-time applications due to its efficiency.