2013 ICCV ICCV 2013

Efficient Image Dehazing with Boundary Constraint and Contextual Regularization

Abstract

suffer from bad visibility. In this paper, we propose an efficient regularization method to remove hazes from a single input image. Our method benefits much from an exploration on the inherent boundary constraint on the transmission function. This constraint, combined with a weighted ms1 sonffnbased contextual regularization, is modeled into an optimization problem to estimate the unknown scene transmission. A quite efficient algorithm based on variable splitting is also presented to solve the problem. The proposed method requires only a few general assumptions and can restore a high-quality haze-free image with faithful colors and fine image details. Experimental results on a variety of haze images demonstrate the effectiveness and efficiency of the proposed method. Keywords-image processing; single image dehazing; visibility enhancement; I. I NTRODUCTION When one takes a picture in foggy weather conditions, the obtained image often suffers from poor visibility. The distant objects in the fog lose the contrasts and get blurred with

🚀 Conference Pioneer — ICCV 2013
🧭 Keyword Pioneer — image dehazing
🐣 Hot Topic Early Bird — image dehazing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Robotics, Security & Privacy