Range Gated Imaging System for Underwater Robotic Vehicle

Tan, Ching Seong; Sluzek, Andrzej; L., G. Seet G.; Jiang, Tianyu

doi:10.1109/oceansap.2006.4393938

Cited by 25 publications

(14 citation statements)

References 14 publications

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“…Another challenge for the future is to develop imaging systems that can eliminate or reduce scattering while imaging. Solutions such as pulse gated cameras and laser emitters are effective [ 164 ], but still expensive.…”

Section: Conclusion and Prospectsmentioning

confidence: 99%

Optical Sensors and Methods for Underwater 3D Reconstruction

Massot-Campos

Oliver-Codina

2015

Sensors

134

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This paper presents a survey on optical sensors and methods for 3D reconstruction in underwater environments. The techniques to obtain range data have been listed and explained, together with the different sensor hardware that makes them possible. The literature has been reviewed, and a classification has been proposed for the existing solutions. New developments, commercial solutions and previous reviews in this topic have also been gathered and considered.

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Section: Conclusion and Prospectsmentioning

confidence: 99%

Optical Sensors and Methods for Underwater 3D Reconstruction

Massot-Campos

Oliver-Codina

2015

Sensors

134

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“…Common measurement parameters for image reliability include mean absolute error, normalized MSE (NMSE), PSNR, and MSE [26]. An SNR over 40 dB provides excellent image quality that is close to that of the original image; an SNR of 30-40 dB typically produces good image quality with acceptable distortion; an SNR of 20-30 dB presents poor image quality; an SNR below 20 dB generates an unacceptable image [27].…”

Section: Performance Measuresmentioning

confidence: 99%

Image denosing in underwater acoustic noise using discrete wavelet transform with different noise level estimation

2020

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In many applications, Image de-noising and improvement represent essential processes in presence of colored noise such that in underwater. Power spectral density of the noise is changeable within a definite frequency range, and autocorrelation noise function is does not like delta function. So, noise in underwater is characterized as colored noise. In this paper, a novel image de-noising method is proposed using multi-level noise power estimation in discrete wavelet transform with different basis functions. Peak signal to noise ratio (PSNR) and mean squared error represented performance measures that the results of this study depend on it. The results of various bases of wavelet such as: Daubechies (db), biorthogonal (bior.) and symlet (sym.), show that denoising process that uses in this method produces extra prominent images and improved values of PSNR than other methods.

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“…There are several existing methods for underwater image processing. In general, these methods can be categorized into two approaches: hardware-based methods [5,6,7,8,9,10] and software-based methods [11,12,13,14]. There are four traditional hardware approaches to underwater imaging: polarization, range-gated imaging, fluorescence imaging [32,33], and stereo imaging [34].…”

Section: Types Of Underwater Imagingmentioning

confidence: 99%

Underwater Optical Image Processing: a Comprehensive Review

Zhang

et al. 2017

Mobile Netw Appl

163

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Abstract:Underwater cameras are widely used to observe the sea floor. They are usually included in autonomous underwater vehicles (AUVs), unmanned underwater vehicles (UUVs), and in situ ocean sensor networks. Despite being an important sensor for monitoring underwater scenes, there exist many issues with recent underwater camera sensors. Because of light's transportation characteristics in water and the biological activity at the sea floor, the acquired underwater images often suffer from scatters and large amounts of noise. Over the last five years, many methods have been proposed to overcome traditional underwater imaging problems. This paper aims to review the state-of-the-art techniques in underwater image processing by highlighting the contributions and challenges presented in over 40 papers. We present an overview of various underwater image-processing approaches, such as underwater image de-scattering, underwater image color restoration, and underwater image quality assessments. Finally, we summarize the future trends and challenges in designing and processing underwater imaging sensors.

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Range Gated Imaging System for Underwater Robotic Vehicle

Cited by 25 publications

References 14 publications

Optical Sensors and Methods for Underwater 3D Reconstruction

Optical Sensors and Methods for Underwater 3D Reconstruction

Image denosing in underwater acoustic noise using discrete wavelet transform with different noise level estimation

Underwater Optical Image Processing: a Comprehensive Review

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