@inproceedings{f1bfea7b7dd64e6db2916784ad0279db,
title = "Haze removal with fusion of local and non-local statistics",
abstract = "Most of the outdoor images suffer from contrast degradation caused by fog and haze. Two statistical frameworks have been proposed in recent years that exploit local (dark channel prior) and non-local (haze-lines) characteristics of hazy images for the estimation of scene configurations and the restoration of scene albedo. Both frameworks show intrinsic limitations due to the basic assumptions they rely on. In this paper we propose a novel dehazing method that combines the advantages of local and non-local dehazing methods. Exploiting their complementary statistical properties, we use the local features to regulate the estimation of non-local haze-lines for a better final restoration at challenging regions. Both quantitative and qualitative results validate the effectiveness of our proposed method over state-of-the-art frameworks.",
keywords = "Dark channel prior, Haze line, Non-local",
author = "Jie Chen and Tan, {Cheen Hau} and Chau, {Lap Pui}",
note = "Funding Information: Jie Chen was with the School of Electrical & Electronic Engineering, Nanyang Technological University. He is now with the Department of Computer Science, Hong Kong Baptist University. The research was partially supported by the ST Engineering-NTU Corporate Lab through the NRF corporate lab {\textcopyright}university scheme. Publisher Copyright: {\textcopyright} 2020 IEEE; 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 ; Conference date: 10-10-2020 Through 21-10-2020",
year = "2020",
month = oct,
language = "English",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings",
}