Underwater video enhancement using multi-camera super-resolution

Quevedo, Eduardo; Delory, Eric; Callicó, Gustavo M.; Tobajas, F.; Sarmiento, Roberto

doi:10.1016/j.optcom.2017.06.054

Cited by 31 publications

(13 citation statements)

References 17 publications

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“…Super resolution can provide better information for understanding the image ahead. Different approaches have been proposed for this work with its own advantages and disadvantages [36,37]. In general, there are two basic methods for fixing low resolution images: one using reconstruction methods and the other learning methods.…”

Section: Super Resolutionmentioning

confidence: 99%

“…In general, there are two basic methods for fixing low resolution images: one using reconstruction methods and the other learning methods. In methods based on reconstructing of the input image, they operate according to the contained information in the image itself and on the basis of rules such as extending the edge of the curvature retention and interpolation between pixels [37].…”

Section: Super Resolutionmentioning

confidence: 99%

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A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing

Moghimi

Mohanna

2019

SN Appl. Sci.

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Nowadays, the underwater optical imaging is used by a wide range of sciences including marine scientists for studying underwater structures and organisms, oil and gas companies, telecommunications to monitor fuel transmission lines and cables, and military centers to detect the sea mines and submarines. Images with non-uniform brightness are visually limited due to low ambient light during imaging or excessive exposure, fogging, hazing, or a combination of these factors. As a result, a process of imaging improvement is highly complex with some conditions. Particularly, this issue is harmful for the underwater environments as well as its highly complexity. In this paper, we improve the underwater images from different environments by exploiting image processing techniques including elimination of fogging in the image, and improvement of contrast with combining super resolution methods which result in significant enhancement of the image quality. To remove fogging in the image enhancement method, a variational-based fusion method was proposed without increasing or decreasing image resolution to increase the adaptability of non-uniform backlight images. This approach is optimized by the bee colony algorithm. Additionally, weighting coefficient selection method is used for super resolution of image after adjusting contrast. The main reason for using hybrid contrast techniques includes the adaptive enhancement and color correction. The bee colony algorithm and weighting coefficient in super resolution due to the lack of hybrid methods in visually improved water images has been the subject of recent researches. The hybrid set has provided more effect on different images at various conditions. Having applied the algorithm set for low-quality visual image set of underwater, some analyses such as PSNR, MSE and SSIM are tested. Compared to similar solutions, the quality is significantly improved and highlighted the exhaustive operation of the algorithm. Applying the presented algorithm in the software part of underwater imaging systems is widely effective for the accurate analysis of underwater images.

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Section: Super Resolutionmentioning

confidence: 99%

Section: Super Resolutionmentioning

confidence: 99%

A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing

Moghimi

Mohanna

2019

SN Appl. Sci.

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“…This prevents less-trained people from acquiring low-cost vehicles. However, considerable work is currently devoted in developing and improving ROV control systems [53] through, for example, vision and image processing [54][55][56], more compact, less energy consuming, and accurate positioning tools [47,[57][58][59], or more advanced and optimized algorithms that can be processed by smaller computers [60,61].…”

Section: Monitoringmentioning

confidence: 99%

Deployment and Maintenance of Wave Energy Converters at the Lysekil Research Site: A Comparative Study on the Use of Divers and Remotely-Operated Vehicles

Remouit

Chatzigiannakou

Bender

et al. 2018

JMSE

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Ocean renewable technologies have been rapidly developing over the past years. However, current high installation, operation, maintenance, and decommissioning costs are hindering these offshore technologies to reach a commercialization stage. In this paper we focus on the use of divers and remotely-operated vehicles during the installation and monitoring phase of wave energy converters. Methods and results are based on the wave energy converter system developed by Uppsala University, and our experience in offshore deployments obtained during the past eleven years. The complexity of underwater operations, carried out by either divers or remotely-operated vehicles, is emphasized. Three methods for the deployment of wave energy converters are economically and technically analyzed and compared: one using divers alone, a fully-automated approach using remotely-operated vehicles, and an intermediate approach, involving both divers and underwater vehicles. The monitoring of wave energy converters by robots is also studied, both in terms of costs and technical challenges. The results show that choosing an autonomous deployment method is more advantageous than a diver-assisted method in terms of operational time, but that numerous factors prevent the wide application of robotized operations. Technical solutions are presented to enable the use of remotely-operated vehicles instead of divers in ocean renewable technology operations. Economically, it is more efficient to use divers than autonomous vehicles for the deployment of six or fewer wave energy converters. From seven devices, remotely-operated vehicles become advantageous.

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“…It provides static and dynamic SR depending on whether the result is one single frame and a video sequence, respectively. The SR algorithm used in this work has been extensively tested by the authors for general-purpose images and video sequences [9,10] and also in specific applications, like underwater images [11] or compressed images [12]. As this SR algorithm is based on the direct processing of the information contained in the input images and not in machine learning techniques, it can be used for any kind of situations (including local and global motion, changes in the illumination among frames, etc.…”

Section: Super-resolutionmentioning

confidence: 99%

Color Reconstruction and Resolution Enhancement Using Super-Resolution

Quevedo¹,

Callicó²

2018

Colorimetry and Image Processing

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Image super-resolution (SR) is a process that enhances the resolution of an image or a set of images beyond the resolution of the imaging sensor. Although there are several superresolution methods, fusion super-resolution techniques are well suited for real-time implementations. In fusion super-resolution, the high-resolution images are reconstructed using different low-resolution-observed images, thereby increasing the high-frequency information and decreasing the degradation caused by the low-resolution sampling process. In terms of color reconstruction, standard reconstruction algorithms usually perform a bilinear interpolation of each color. This reconstruction performs a strong low-pass filtering, removing most of the aliasing present in the luminance signal. In this chapter, a novel way of color reconstruction is presented by using super-resolution in order to reconstruct the missing colors.

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Underwater video enhancement using multi-camera super-resolution

Cited by 31 publications

References 17 publications

A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing

A joint adaptive evolutionary model towards optical image contrast enhancement and geometrical reconstruction approach in underwater remote sensing

Deployment and Maintenance of Wave Energy Converters at the Lysekil Research Site: A Comparative Study on the Use of Divers and Remotely-Operated Vehicles

Color Reconstruction and Resolution Enhancement Using Super-Resolution

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