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Joint dual-teacher distillation and unsupervised fusion for unpaired real-world image dehazing
Existing learning-based dehazing algorithms struggle to deal with real world hazy images for lack of paired clean data. Moreover, most dehazing...
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Fuzzy histogram equalization of hazy images: a concept using a type-2-guided type-1 fuzzy membership function
Hazy conditions, which are one of the most deleterious atmospheric scenarios, deteriorate the accuracy of autonomous vision systems during...
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Single Image Dehazing Techniques for Different Types of Hazy Images
Single image dehazing is a big challenge in practical life due to the presence of a single input image for removing haze from hazy images. It has...
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A Novel Approach for Object Recognition in Hazy Scenes: Integrating YOLOv7 Architecture with Boundary-Constrained Dehazing
To improve the detection of objects in the haze environment, we have integrated boundary delimitation techniques into the YOLOv7 architecture in this...
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Hazy Removal via Graph Convolutional with Attention Network
Most deep learning based single image dehazing methods use convolutional neural networks (CNN) to extract features, however CNN can only capture...
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Smoke removal technique of industrial scene images based on second-generation wavelets and dark channel prior model
The world has seen a ground-breaking development in the utilization of digital images and their applications in modern society. Practically, digital...
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Dehazing of Multispectral Images Using Contrastive Learning In CycleGAN
Picture dehazing is a necessary aspect in computer vision, especially when employed with surveillance and satellite data. In this study, we provide a...
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A New Multi-level Hazy Image and Video Dataset for Benchmark of Dehazing Methods
The changing level of haze is one of the main factors which affects the success of the proposed dehazing methods. However, there is a lack of...
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Dark Channel Prior-Based Single-Image Dehazing Using Type-2 Fuzzy Sets for Edge Enhancement in Dehazed Images
The process of image dehazing is known to have a significant impact in the field of computer vision. It has been found to have practical applications...
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An Error Dependent Enhancement Method for Images Captured in Dense Fog
Fog and haze naturally or artificially appearing in the environment, limit human visibility. As a way of improving the visibility, digital images are...
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Drfnet: dual stream recurrent feature sharing network for video dehazing
The primary effects of haze on captured images/frames are visibility degradation and color disturbance. Even though extensive research has been done...
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Vehicle License Plate Image Preprocessing Strategy Under Fog/Hazy Weather Conditions
The automatic license plate recognition (ALPR) of a vehicle is a vital requirement in modern society. Recently, the degree of obscureness has been...
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Dual-branch feature fusion dehazing network via multispectral channel attention
Image information degradation significantly complicates single-image dehazing. Despite the noteworthy progress of learning-based methods in removing...
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Single Image Dehazing Using CNN
Particulate matter in the atmosphere obscures the visibility of the atmosphere, causing a condition known as haze. Other natural phenomena like mist,...
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Single Encoder and Decoder-Based Transformer Fusion with Deep Residual Attention for Restoration of Degraded Images and Clear Visualization in Adverse Weather Conditions
Removing adverse weather conditions from images, such as haze, fog, rain, and snowfall, is a significant issue in several scenarios. Many techniques...
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Video quality enhancement using different enhancement and dehazing techniques
Video in an outdoor environment suffers from the haze problem due to smoke, dust, and other particles in the atmosphere. The quality of video under...
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Graph Disentangled Representation Based Semi-supervised Single Image Dehazing Network
Single image dehazing algorithms aim to recover a clear image from a hazy one. Most learning-based single image dehazing algorithms are trained on...
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A novel neutrosophic divergence score for enhancement of mammogram images
Medical images, especially mammogram images, have low contrast and brightness so mammogram image enhancement is very much necessary in diagnosing...
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Depth color correlation-guided dark channel prior for underwater image enhancement
Due to the attenuation of underwater light, obtained images often suffer from low contrast, noise interference, and hazy content. In the field of...
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Image Enhancement of Underwater Images Using Deep Learning Techniques
In the present era enhancing the under image quality play a major role for research purpose and ocean exploration. The market for high-quality...