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DENSECL: Haze Mitigation Using Dense Blocks and Contrastive Loss Regularization...

by Somosmita Mitra, Byung H Park
Publication Type
Conference Paper
Book Title
IEEE International Conference on Image Processing (ICIP) 2023
Publication Date
Publisher Location
New Jersey, United States of America
Conference Name
2023 IEEE International Conference on Image Processing (ICIP 2023)
Conference Location
Kuala Lumpur, Malaysia
Conference Sponsor
Conference Date

Haze, which occurs as a result of the scattering of light in the atmosphere by small particles, diminishes the visibility of scene objects, inflicting important image applications such as object detection. To address the problem, this paper introduces a new physics-based end-to-end deep learning approach to haze mitigation in outdoor scenes, including those in airborne images. The proposed model named DenseCL is designed with dense blocks and adopts a contrastive loss function as an additional regularization. The model also maintains the cycle consistency by remapping the dehazed outputs into a hazy image using the physics-based light scattering function. DenseCL has been trained with publicly available outdoor images and demonstrates outstanding performance on outdoor, indoor, and remotely sensed nonhomogeneous haze satellite images.