Results 21 to 30 of about 303 (154)
GUSL-Dehaze: A Green U-Shaped Learning Approach to Image Dehazing
2025 IEEE 8th International Conference on Multimedia Information Processing and Retrieval (MIPR)Image dehazing is a restoration task that aims to recover a clear image from a single hazy input. Traditional approaches rely on statistical priors and the physics-based atmospheric scattering model to reconstruct the haze-free image. While recent state-of-the-art methods are predominantly based on deep learning architectures, these models often ...
Mahtab Movaheddrad +2 more
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Let Segment Anything Help Image Dehaze [PDF]
, 2023 The large language model and high-level vision model have achieved impressive performance improvements with large datasets and model sizes. However, low-level computer vision tasks, such as image dehaze and blur removal, still rely on a small number of ...
Feng, Huajun +4 more
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A novel simulation for polarization dehazing
IEEE Signal Processing Letters, 2023 Haze and fog, as severe weather conditions, have absorbing and scattering effects on the optical images, severely affecting image quality. Polarization-based dehazing algorithms can estimate the original radiance distribution of the scene through the polarization of skylight and transmitted light.
Changda Yan +4 more
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IMAGE DEHAZING USING FAST ITERATIVE DOMAIN GUIDED IMAGE FILTERING WITH GRAY WORLD OPTIMIZATION [PDF]
Proceedings on Engineering SciencesWhen remote sensing photos are taken, they are often captured in hazy circumstances such as fog, snow, thin clouds, dust, and other similar situations, which causes the contrast in the image to decrease.
Bhaskar Reddy Bada +3 more
doaj +1 more source
Enhanced Variational Image Dehazing [PDF]
SIAM Journal on Imaging Sciences, 2015 Images obtained under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and ...
Adrian Galdran +3 more
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Enhancement of Low Contrast Images Based on Effective Space Combined with Pixel Learning
Information, 2017 Images captured in bad conditions often suffer from low contrast. In this paper, we proposed a simple, but efficient linear restoration model to enhance the low contrast images.
Gengfei Li, Guiju Li, Guangliang Han
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Single-Image Dehazing Using Extreme Reflectance Channel Prior
IEEE Access, 2021 Image dehazing algorithms based on dark channel prior principle have achieved good results for most scenes. However, the popular dark channel prior tends to underestimate transmissions of bright areas or objects, such as the skies, white areas and self ...
Yutong Zhang +6 more
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Nighttime Image Dehazing Based on Point Light Sources
Applied Sciences, 2022 Images routinely suffer from quality degradation in fog, mist, and other harsh weather conditions. Consequently, image dehazing is an essential and inevitable pre-processing step in computer vision tasks.
Xin-Wei Yao +4 more
doaj +1 more source
Improved reflection removal with dark channel prior
, 2021 This article proposed an idea that the quality of reflection removal can be improved by preprocess the input image with a dehaze method (which is dark channel prior in this paper)
yuan liu
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Sea-surface object detection scheme for USV under foggy environment [PDF]
, 2021 960-968Sea-surface target detection is investigated for the visual image-based autonomous control of an Unmanned Surface Vessel (USV). A traditional way is to dehaze for sea-surface images in the previous target detection algorithms.
Zhang, T +4 more
core +1 more source