Results 31 to 40 of about 1,385 (183)

Mapping and Deep Analysis of Image Dehazing: Coherent Taxonomy, Datasets, Open Challenges, Motivations, and Recommendations.

International Journal of Interactive Multimedia and Artificial Intelligence, 2021
Our study aims to review and analyze the most relevant studies in the image dehazing field. Many aspects have been deemed necessary to provide a broad understanding of various studies that have been examined through surveying the existing literature ...
Karrar Hameed Abdulkareem, Nureize Arbaiy, Zainab Hussein Arif, Mohammed Nasser Al-Mhiqani, Mazin Abed Mohammed, Seifedine Kadry, Zaid Abdi Alkareem Alyasseri   +6 more
doaj   +1 more source

AED-Net: A Single Image Dehazing

IEEE Access, 2022
In the past decade, significant research effort has been directed toward developing single-image dehazing algorithms. Despite this effort, dehazing continues to present a challenge, particularly in complex real-world cases.
Sargis A. Hovhannisyan, Hayk A. Gasparyan, Sos S. Agaian, Art Ghazaryan   +3 more
doaj   +1 more source

Single Image Dehazing Using Wavelet-Based Haze-Lines and Denoising

IEEE Access, 2021
Haze reduces the contrast of an image and causes the loss in colors, which has a negative effect on the subsequent object detection; therefore, single image dehazing is a challenging visual task.
Wei-Yen Hsu, Yi-Sin Chen
doaj   +1 more source

Dehazing algorithm for complex environment video images considering visual communication effects

Journal of Radiation Research and Applied Sciences
The communication effect of outdoor computer vision systems is closely related to the dehazing performance of video images. Currently, video image restoration methods in complex environments are still in an urgent development stage.
Yisa Yu, Jianwen Li
doaj   +1 more source

A Bayesian Framework for Single Image Dehazing considering Noise

The Scientific World Journal, 2014
The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed.
Dong Nan, Du-yan Bi, Chang Liu, Shi-ping Ma, Lin-yuan He   +4 more
doaj   +1 more source

Single image dehazing based on hazy features extraction and enhancement network

Journal of Measurement Science and Instrumentation, 2023
Convolutional neural network is developing rapidly in image processing. Most image dehazing algorithms only focus on dehazing but neglect the overall quality of dehazing image, which leads to problems such as loss of information blurred texture, etc.
ZHANG Jinlong, YANG Yan
doaj  

Nighttime Dehazing with a Synthetic Benchmark [PDF]

Proceedings of the 28th ACM International Conference on Multimedia, 2020
Increasing the visibility of nighttime hazy images is challenging because of uneven illumination from active artificial light sources and haze absorbing/scattering. The absence of large-scale benchmark datasets hampers progress in this area. To address this issue, we propose a novel synthetic method called 3R to simulate nighttime hazy images from ...
Jing Zhang 0037, Yang Cao 0010, Zheng-Jun Zha, Dacheng Tao   +3 more
openaire   +3 more sources

Large‐scale characterization of horizontal forest structure from remote sensing optical images

Remote Sensing in Ecology and Conservation, Volume 12, Issue 4, Page 611-628, August 2026.
Sub‐meter resolution remote sensing data and tree crown segmentation techniques hold promise in offering detailed information that can support the characterization of forest structure from a horizontal perspective, offering new insights in the tree crown structure at scale.
Xin Xu, Martin Brandt, Xiaowei Tong, Maurice Mugabowindekwe, Yuemin Yue, Sizhuo Li, Qiue Xu, Siyu Liu, Florian Reiner, Kelin Wang, Zhengchao Chen, Yongqing Bai, Rasmus Fensholt   +12 more
wiley   +1 more source

Task‐Aligned Haze Removal With Semantic‐Aware Fusion and Contrast Self‐Correction

CAAI Transactions on Intelligence Technology, Volume 11, Issue 4, Page 978-993, August 2026.
ABSTRACT Adverse haze conditions introduce complex degradations that obscure scene details and distort structural cues critical for object detection, posing persistent challenges for vision‐based sensing systems. Although existing haze removal methods have achieved notable improvements in visual clarity, their optimisation objectives are often ...
Jinbin Wang, Aiping Yang, Guosong Jiang, Wenlong Yu, Dongwei Ren, Qinghua Hu   +5 more
wiley   +1 more source

DeepVideoDehazeNet: A Comprehensive Deep Learning Approach for Video Dehazing Using Diverse Datasets [PDF]

International Journal of Mathematical, Engineering and Management Sciences
Video dehazing is a technique commonly used to enhance the quality of videos that appear hazy or degraded due to factors like air scattering and light absorption.
Sandeep Vishwakarma, Anuradha Pillai, Deepika Punj   +2 more
doaj   +1 more source