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[IEEE 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) - Las Vegas, NV (2018.4.8-2018.4.10)] 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) - Underwater Image Restoration using Deep Networks to Estimate Background Light and Scene Depth
摘要： Images taken underwater often suffer color distortion and low contrast because of light scattering and absorption. An underwater image can be modeled as a blend of a clear image and a background light, with the relative amounts of each determined by the depth from the camera. In this paper, we propose two neural network structures to estimate background light and scene depth, to restore underwater images. Experimental results on synthetic and real underwater images demonstrate the effectiveness of the proposed method.
关键词： depth estimation,image restoration,convolutional neural networks,Underwater images
更新于2025-09-23 15:21:21
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[IEEE OCEANS 2018 MTS/IEEE Charleston - Charleston, SC, USA (2018.10.22-2018.10.25)] OCEANS 2018 MTS/IEEE Charleston - Geometric Distortion Correction for the Underwater Images
摘要： Non-metric cameras have been widely used in applications of obtaining geometric information of the underwater objects using either digital photogrammetric approaches or computer vision algorithms. All the underwater images exhibit significant geometric distortions caused by lens distortions and light refraction in underwater imaging, which must be geometrically corrected. In this paper, a geometric distortion correction method for the underwater images is proposed, which uses the sets of distortion parameters obtained through the iterative camera calibration to determine the position relationship between the original images and the final corrected images, and then the gray values of the final corrected images are directly resampled from the original images. The GoPro Hero 5 Black calibration results show that the final accuracies are close to 0 pixel after three iterations; all the final distortion parameters calculated with the iterative calibration method are decreased after several iterations and can be ignored. By contrast, the original image was corrected well with the three sets of distortion parameters calculated with the iterative calibration method. An example shows that the successful generation of point clouds illustrates the effectiveness of the geometric correction. The proposed correcting method provides a technique not only to greatly reduce the distortion through applying a series of distortion parameters but also preserve the image quality through a smart resampling way.
关键词： sets of distortion parameters,once resampling,iterative camera calibration,underwater images,geometric correction
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) - Chengdu, China (2019.12.20-2019.12.22)] 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) - Research on Sparse Code Shrinkage denoise in Underwater 3D Laser Scanning Images
摘要： Noise removal is the pre-stage and essential step for many image processing tasks. Sometimes it is hard to have correct exposure for camera in underwater environment. In general, we need to have long exposure time to collect the weak light signal which increase the background electrical noise and higher than the signal. Underwater laser scanning is such special case with white laser stripe and dark background images. Hence, noise including which dots, lumps have heavy impact to our laser image. This paper discuss underwater laser scanning image denoise and presents the method based on Sparse code shrinkage algorithm to reduce such noise effect in ?nal reconstructed 3D model. The comparative study using natural and real 3D underwater scanning images is presented on the experimental section.
关键词： SCS,3D laser scanning,Image denoise,Underwater Images
更新于2025-09-19 17:13:59