scholarly journals A Contrast-Guided Approach for the Enhancement of Low-Lighting Underwater Images

2019 ◽  
Vol 5 (10) ◽  
pp. 79 ◽  
Author(s):  
Tunai Porto Marques ◽  
Alexandra Branzan Albu ◽  
Maia Hoeberechts
Keyword(s):  
Automated Analysis ◽  
Local Contrast ◽  
Single Image ◽  
Image Dehazing ◽  
Artificial Lighting ◽  
Lighting Conditions ◽  
Underwater Image ◽  
Low Visibility ◽  
Contrast Information ◽  
New Framework

Underwater images are often acquired in sub-optimal lighting conditions, in particular at profound depths where the absence of natural light demands the use of artificial lighting. Low-lighting images impose a challenge for both manual and automated analysis, since regions of interest can have low visibility. A new framework capable of significantly enhancing these images is proposed in this article. The framework is based on a novel dehazing mechanism that considers local contrast information in the input images, and offers a solution to three common disadvantages of current single image dehazing methods: oversaturation of radiance, lack of scale-invariance and creation of halos. A novel low-lighting underwater image dataset, OceanDark, is introduced to assist in the development and evaluation of the proposed framework. Experimental results and a comparison with other underwater-specific image enhancement methods show that the proposed framework can be used for significantly improving the visibility in low-lighting underwater images of different scales, without creating undesired dehazing artifacts.

Single Image Dehazing by Predicting Atmospheric Scattering Parameters

2020 ◽  
Vol 2020 (1) ◽  
pp. 74-77
Author(s):  
Simone Bianco ◽  
Luigi Celona ◽  
Flavio Piccoli
Keyword(s):  
Reference Image ◽  
Single Image ◽  
Scattering Parameters ◽  
Image Dehazing ◽  
Atmospheric Scattering ◽  
Local Structures ◽  
Full Reference ◽  
Reconstruction Quality ◽  
Single Image Dehazing

In this work we propose a method for single image dehazing that exploits a physical model to recover the haze-free image by estimating the atmospheric scattering parameters. Cycle consistency is used to further improve the reconstruction quality of local structures and objects in the scene as well. Experimental results on four real and synthetic hazy image datasets show the effectiveness of the proposed method in terms of two commonly used full-reference image quality metrics.

scholarly journals Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Fusion Method ◽  
Formation Model ◽  
Low Contrast ◽  
White Balance ◽  
Multi Scale ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

Single image dehazing using a new color channel

2021 ◽  
Vol 74 ◽  
pp. 103008
Author(s):  
Geet Sahu ◽  
Ayan Seal ◽  
Ondrej Krejcar ◽  
Anis Yazidi
Keyword(s):  
Single Image ◽  
Color Channel ◽  
Image Dehazing ◽  
Single Image Dehazing

Deep Retinex Network for Single Image Dehazing

2021 ◽  
Vol 30 ◽  
pp. 1100-1115
Author(s):  
Pengyue Li ◽  
Jiandong Tian ◽  
Yandong Tang ◽  
Guolin Wang ◽  
Chengdong Wu
Keyword(s):  
Single Image ◽  
Image Dehazing ◽  
Single Image Dehazing

Errors of In Situ Illuminance Measurements

2016 ◽  
Vol 824 ◽  
pp. 676-683
Author(s):  
Michaela Hlásková ◽  
Lenka Gábrová ◽  
František Vajkay
Keyword(s):  
Measurement Errors ◽  
Daily Basis ◽  
Lighting Design ◽  
Public Health Authority ◽  
Construction Work ◽  
Measurement Instruments ◽  
Artificial Lighting ◽  
Lighting Conditions ◽  
Overcast Sky

Lighting conditions in buildings are verified by experts on a daily basis. Such verifications may be done at several phases in various ways. In the field of daylighting, it is common to make an assessment within the pre-design and in-design phases of a construction work throughout calculations, only rarely by measurements. This approach is the opposite of artificial lighting design, which is done within the in-design phase by calculations and is verified by measurements in post-realization phase. The verification of artificial lighting design is required by the building and public health authority otherwise buildings cannot be approved to use. In the field of daylighting, measurements could be performed as well, nevertheless those are often problematic because regulations usually require fulfilments of the daylight factor which can be determined only under CIE overcast sky. Howbeit, both artificial lighting and daylighting measurements are influenced by many errors, e.g. errors of light measurement instruments, measurement conditions, measurement methods and human factor. The paper is focused on this aspect of lighting design, more specifically on the daylighting measurement errors.

scholarly journals A Fast Single-Image Dehazing Algorithm Based on Dark Channel Prior and Rayleigh Scattering

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 73330-73339 ◽  
Author(s):  
Jehoiada Jackson ◽  
She Kun ◽  
Kwame Obour Agyekum ◽  
Ariyo Oluwasanmi ◽  
Parinya Suwansrikham
Keyword(s):  
Rayleigh Scattering ◽  
Dark Channel Prior ◽  
Single Image ◽  
Image Dehazing ◽  
Dark Channel ◽  
Single Image Dehazing

Single Image Dehazing via Region Adaptive Two-shot Network

2021 ◽  
pp. 1-1
Author(s):  
Hui Li ◽  
Qingbo Wu ◽  
King Ngi Ngan ◽  
Hongliang Li ◽  
Fanman Meng
Keyword(s):  
Single Image ◽  
Image Dehazing ◽  
Single Image Dehazing
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