APSDCP-Net: Adaptive Patch-Size Dark Channel Prior Network for Single Image Dehazing
Journal
Proceedings - 2025 21st IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2025
Start Page
1
End Page
5
ISBN (of the container)
979-833158907-3
Date Issued
2026-02-19
Author(s)
Abstract
Single image dehazing is a critical computer vision task that aims to recover a clear image from a hazy input. In recent years, both learning-based and prior-based dehazing methods have been rigorously developed, yet each has limitations in haze removal performance. In this work, we propose the Adaptive Patch Size Dark Channel Prior Network (APSDCP-Net), a hybrid dehazing network that combines the dark channel prior with a learnable architecture. By reframing the dehazing problem as a patch size selection task, the proposed model combines multiple patch-sizes dark channels using learned soft weights, resulting in more accurate transmission estimation and enhanced dehazing performance. Experiments show that the proposed APSDCP-Net achieves superior performance compared to state-of- the-art dehazing methods.
Event(s)
2025 21st IEEE Asia Pacific Conference on Circuits and Systems, APCCAS 2025
Subjects
dark channel prior
end-to-end hybrid learning
patch size selection
single image dehazing
Publisher
IEEE
Type
conference paper