Enhanced Image Dehazing Using Bright and Dark Channel Prior

ABSTRACT - Visibility degradation caused by haze presents a major challenge for computer vision systems in outdoor environments. This project introduces an enhanced image dehazing method based on Bright and Dark Channel Prior (BDCP), an improvement over traditional dark channel technique. By incorporating both bright and dark channel information, the method more effectively estimates the transmission map and atmospheric light, resulting in clearer and more natural dehazed images. The proposed algorithm refines visual quality through a fusion-based enhancement and edge-preserving filtering. Extensive experiments demonstrate that this approach significantly outperforms conventional methods in terms of contrast restoration and color fidelity, particularly under dense haze conditions. Key Words: Image Dehazing, Dark Channel Prior, Bright Channel Prior, Transmission Estimation, Atmospheric Light, Visibility Restoration, Haze Removal, Image Enhancement.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-29
DOI
https://doi.org/10.55041/ijsrem49041
Primary Topic
Image Enhancement Techniques
Type
article
Field-Weighted Citation Impact
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article

Enhanced Image Dehazing Using Bright and Dark Channel Prior

Sana Subramanyam
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Image Enhancement Techniques
article

Enhanced Image Dehazing Using Bright and Dark Channel Prior

Sana Subramanyam
article en

Abstract

ABSTRACT - Visibility degradation caused by haze presents a major challenge for computer vision systems in outdoor environments. This project introduces an enhanced image dehazing method based on Bright and Dark Channel Prior (BDCP), an improvement over traditional dark channel technique. By incorporating both bright and dark channel information, the method more effectively estimates the transmission map and atmospheric light, resulting in clearer and more natural dehazed images. The proposed algorithm refines visual quality through a fusion-based enhancement and edge-preserving filtering. Extensive experiments demonstrate that this approach significantly outperforms conventional methods in terms of contrast restoration and color fidelity, particularly under dense haze conditions. Key Words: Image Dehazing, Dark Channel Prior, Bright Channel Prior, Transmission Estimation, Atmospheric Light, Visibility Restoration, Haze Removal, Image Enhancement.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 90%
Image Enhancement Techniques
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