Factors such as scattering and absorption of light by suspended particles and lack of light in deep water exist in complex underwater environments, leading to visual degradation effects such as loss of underwater image features, colour deviation and contrast reduction. With the development of artificial intelligence, deep neural networks are widely used in the field of computer vision and show their powerful brain-like separation (local information processing) and integration (global information processing) processing capabilities. In this paper, we use the visual saliency model to construct a Gaussian pyramid of luminance, orientation, edge and colour applicable to underwater degraded images to obtain shallow image features of underwater images. Combined with the VGG16 convolutional neural network model to construct a progressive enhancement neural network based on deep learning, which in turn improves the high-dimensional saliency features of underwater degraded images. The experimental results show that the enhanced underwater image features of this algorithm have better detail retention and the colour is more in line with the human eye vision, and the experimental results of the objective indexes are better than the comparison algorithm.
In a high-power underwater wireless optical communication (UWOC) system, the bandwidth limitations of high-power optical sources and high-sensitivity detectors and the multipath effect of seawater channels can cause intersymbol interference, which seriously affects the performance of the UWOC system. Based on the attenuation characteristics and time-domain broadening characteristics of underwater wireless optical signals, a dual-mode adaptive switching blind equalization algorithm is proposed; it combines the variable step size constant-to-mode fractional spaced equalizer (FSE) algorithm and the decision directed least-mean-square mode-FSE algorithm to improve the performance of long-distance UWOC systems. Simulations show that the proposed algorithm has antinoise performance under different seawater qualities. In particular, with a bit error rate performance of 10 − 4 in coastal seawater, the signal-to-noise ratio of the proposed algorithm is 5.2 dB lower than the traditional constant-to-mode decision directed least-mean-square algorithm and 9.2 dB lower than that when the algorithm is not equalized.
The performance analysis of underwater optical wireless communication (UOWC) with digital pulse interval modulation in anisotropy oceanic turbulence environment is investigated. We aim at the packet error rate (PER) of UOWC system using Gaussian-Schell model beam and avalanche photodiode receiver. Based on the generalized Huygens-Fresnel principle, the received light intensity is derived. The effects of PER variations with anisotropy factor, modulation order of DPIM, coherent parameters of the GSM and the ratio of temperature to salinity contributions to the refractive index spectrum are investigated.
In this thesis, we designed and experimentally demonstrated a high-power high-speed underwater optical wireless communication (UOWC) system with wavelength conversion construction. External modulation based on 1064nm laser is used for high-speed information communication, as well as the optical amplifier is used to obtain enough optical power of 1064nm laser. After that, according to the quasi-phase-matching (QPM) conditions, the PPLN optical structure is designed to improve the wavelength conversion efficiency for achieving higher 532nm laser output power in 24.5℃~40°C. Compared to the 532nm LD modulation system, this system can output 1.4W 532nm laser power in 100Mbps. This system experiments in single link 100m water tap of the attenuation coefficient 0.73dB/m equivalent to the clear ocean, and the measured bit error rate (BER) is 6.2×10-6 in 100Mbps pseudo-random binary sequence (PRBS) data without the forward error correction (FEC). Based on receiver sensitivity and the seawater channel optical transmission model, the transmission performance was predicted to be 340m@100Mbps and 100m@2Gbps in the attenuation coefficient equivalent to pure seawater.
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