Results 81 to 90 of about 16,734,778 (159)
IET Image Processing, Volume 20, Issue 1, January/December 2026.This study proposes Swin‐attention‐enhanced atrous spatial pyramid pooling (ASPP)‐attention‐squeeze‐and‐excitation (SE) uncertainty‐aware U‐Net++ (SAASU‐UNet++), a novel hybrid deep learning framework for breast tumour segmentation in ultrasound images.
Rahul Singh +6 more
wiley +1 more source
Multi-level fusion dehazing network based on learning of hazy layers
Journal of Measurement Science and Instrumentation, 2023 Aiming at the problems such as color cast and incomplete haze removal in dehazing algorithms, a multi-level feature fusion network based on the learning of hazy layers is proposed for single image dehazing.
WANG Rong, YANG Yan
doaj
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
AMSA-Net: attention-based multi-scale feature aggregation network for single image dehazing
Frontiers in NeuroroboticsProblemDeep learning technology promotes the development of single-image dehazing. However, many existing methods fail to fully consider the haze density and its spatial distribution, which limits the improvement of dehazing performance.Proposed ...
Shanqin Wang +3 more
doaj +1 more source
Pseudo-polarimetric Method for Dense Haze Removal
IEEE Photonics Journal, 2019 The scattering and absorption by the existing particles in turbid media is severely degrading the image quality and decreasing the visibility distance, especially in dense turbid media.
Xiaobo Li +6 more
doaj +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
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
Refining Transmission Map and Air Light for Efficient Single Image Dehazing
IEEE AccessMany dehazing methods have been presented by many researchers either on single hazy images or multiple images like videos. Single image dehazing is a very challenging problem, since there is no ground truth image and/or depth map. Beyond many traditional
Yucel Cimtay, Gokce Nur Yilmaz
doaj +1 more source
Image Dehazing Using Residual-Based Deep CNN
IEEE Access, 2018 There is a series of image degradation in the image acquired in haze and other weather. The single image dehazing is a challenging and ill-posed problem.
Jinjiang Li, Guihui Li, Hui Fan
doaj +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