Results 91 to 100 of about 11,243,828 (208)
RSDhazer: Residual Shallow‐Deep Network for Efficient Single‐Image Dehazing
IET Image Processing, Volume 20, Issue 1, January/December 2026.We introduce RSDhazer, a lightweight and efficient end‐to‐end dehazing network designed to handle the complexity of haze removal while maintaining a low computational cost. The proposed RSDhazer comprises three distinct feature extraction blocks that extract shallow and deep features from input images and propagate them through the network without ...
Syeda Rabail Zahra +6 more
wiley +1 more source
Color Channel Transfer for Image Dehazing
, 2019 In this letter we introduce a simple but effective concept, Color Channel Transfer (CCT), that is able to substantially improve the performance of various dehazing techniques.
Ancuti, Cosmin +3 more
core +1 more source
IET Image Processing, Volume 20, Issue 1, January/December 2026.Sand‐dust degradation significantly reduces visibility, colour fidelity, and structural detail in outdoor imaging systems. This paper proposes TradMS‐ResGAN, a sequential multi‐stage restoration framework that combines a physically interpretable enhancement pipeline with a lightweight multi‐scale residual GAN for refined texture reconstruction and ...
Muhammad Masood +2 more
wiley +1 more source
Single Remote Sensing Image Dehazing Using a Prior-Based Dense Attentive Network
, 2019 Remote sensing image dehazing is an extremely complex issue due to the irregular and non-uniform distribution of haze. In this paper, a prior-based dense attentive dehazing network (DADN) is proposed for single remote sensing image haze removal.
Ziqi Gu +3 more
core +1 more source
UDAPA: A Lightweight Adapter for Robust Underwater Image Enhancement via Input‐Side Alignment
IET Image Processing, Volume 20, Issue 1, January/December 2026.We propose UDAPA, a lightweight adapter framework for robust underwater image enhancement via input‐side alignment. Rather than modifying the pre‐trained backbone, UDAPA adapts degraded inputs toward a feature distribution that is more compatible with the frozen pre‐trained model.
Hui Zhang, Zhaolong Gao, Jinjiang Li
wiley +1 more source
A joint image dehazing and segmentation model
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2019 Objects and their feature identification in hazy or foggy weather conditions has been of interest in the last decades. Improving image visualization by removing weather influence factors for easy image postprocessing, such as object detection, has benefits for human assistance systems.
Haider Ali 0004 +3 more
openaire +1 more source
DUNet: a novel dehazing model based on outdoor images
Frontiers in Plant ScienceImage dehazing technology is widely utilized in outdoor environments, especially in precision agriculture, where it enhances image quality and monitoring accuracy.
Wei Zhao +10 more
doaj +1 more source
IHDCP: Single Image Dehazing Using Inverted Haze Density Correction Prior
Image dehazing, a crucial task in low-level vision, supports numerous practical applications, such as autonomous driving, remote sensing, and surveillance.
Li, Tao +5 more
core +1 more source
Density-Aware Diffusion Model for Efficient Image Dehazing
Existing image dehazing methods have made remarkable progress. However, they generally perform poorly on images with dense haze, and often suffer from unsatisfactory results with detail degradation or color distortion. In this paper, we propose a density-
Bai, Wenxu, Xiao, Chunxia, Zhang, Ling
core +1 more source
Color Image Dehazing using the Near-Infrared [PDF]
, 2009 In landscape photography, distant objects often appear blurred with a blue color cast, a degradation caused by atmospheric haze. To enhance image contrast, pleasantness and information content, dehazing can be performed.
Sabine Susstrunk +5 more
core +2 more sources