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Underwater vision enhancement method and device based on cascaded deep network

A deep network and visual enhancement technology, applied in image enhancement, neural learning methods, biological neural network models, etc., can solve the problems of low modeling accuracy and high complexity of parameter estimation, and achieve improved effect, effect improvement, and accuracy. improved effect

Pending Publication Date: 2020-07-14
CHINA AGRI UNIV
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Problems solved by technology

[0005] Embodiments of the present invention provide an underwater vision enhancement method and device based on a cascaded deep network by means of an underwater optical imaging physical model and a convolutional neural network to solve the problem of model establishment in existing underwater image enhancement methods. Problems with high parameter estimation complexity and low modeling accuracy

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  • Underwater vision enhancement method and device based on cascaded deep network
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  • Underwater vision enhancement method and device based on cascaded deep network

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Embodiment Construction

[0045] In order to make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be described clearly and completely in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0046] Existing methods for enhancing underwater degraded images generally have the problems of high parameter estimation complexity and low modeling accuracy when the image enhancement model is established. In this regard, the embodiment of the present invention provides an underwater vision enhancement method based on a cascaded dee...

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Abstract

The embodiment of the invention provides an underwater vision enhancement method and device based on a cascaded deep network. The method comprises: determining an underwater degraded image; inputtingthe underwater degraded image into an underwater image enhancement model, and outputting an enhanced image corresponding to the underwater degraded image, wherein the underwater image enhancement model is obtained by training based on sample underwater degraded images and enhanced image tags corresponding to the sample underwater degraded images, the underwater image enhancement model is trained by adopting a network established by two stages of convolutional neural networks, and each stage of convolutional neural network is composed of five convolutional layers and three dense connection layers. According to the method and device provided by the embodiment of the invention, the accuracy of underwater image enhancement modeling is improved, and the effect of underwater image enhancement isalso improved.

Description

Technical field [0001] The invention relates to the technical field of image enhancement, in particular to an underwater vision enhancement method and device based on a cascaded deep network. Background technique [0002] In recent years, underwater image enhancement has received extensive attention in the fields of image processing and computer vision. Due to the complexity of the underwater environment and lighting conditions, underwater image enhancement has become a challenging problem. Under normal circumstances, underwater images are subject to wavelength-dependent absorption and scattering, resulting in image degradation, including fogging caused by the scattering of light by small suspended particles in water, and water absorption caused by the absorption of light of different wavelengths. Distortion of the image color. [0003] The traditional underwater image enhancement method based on the physical imaging model is to estimate the transmittance of underwater imaging an...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06T5/77
Inventor 安冬于晓宁王雅倩位耀光李道亮
Owner CHINA AGRI UNIV
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