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Underwater image enhancement method and system based on structure decomposition and storage medium

An underwater image and construction method technology, which is applied in image enhancement, image data processing, neural learning methods, etc., can solve the problems of insufficient image clarity, loss, considering the cycle consistency of input images and generated images, etc.

Inactive Publication Date: 2021-04-16
COLLEGE OF SCI & TECH NINGBO UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In the above scheme, CycleGAN’s generative confrontation network is used, and the non-paired training set is used for training to realize the conversion of two image styles; but only the cycle consistency loss of the input image and the generated image is considered, so the image generated by this method is clear degree is still not up to the required requirements, so there is room for improvement

Method used

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  • Underwater image enhancement method and system based on structure decomposition and storage medium
  • Underwater image enhancement method and system based on structure decomposition and storage medium
  • Underwater image enhancement method and system based on structure decomposition and storage medium

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Experimental program
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Embodiment 1

[0092] An embodiment of the present application provides an underwater image enhancement method based on structural decomposition, including: acquiring the original first underwater image; decomposing the original first underwater image into first high-frequency information HFI and first low-frequency information LFI The UWCNN-SD network model that completes the training includes a preliminary enhanced network model, and the preliminary enhanced network model includes an LF enhanced network model and a HF enhanced network model; the first high-frequency information HFI is input into the HF enhanced network model that completes the training to Obtain the first enhanced high-frequency information after the enhancement, input the first low-frequency information LFI into the LF enhanced network model that has completed the training to obtain the first enhanced low-frequency information after the enhancement; combine the first enhanced high-frequency information after the enhancement...

Embodiment 2

[0152] Such as Figure 4 As shown, the difference from Embodiment 1 is that the UWCNN-SD network model that has been trained also includes a refined network model.

[0153] Among them, the refined network model includes seven sequentially connected convolutional layers, BN and activation functions, which are constructed as follows:

[0154] (3×3)×3×32 convolution layer (step size 1, no padding, BN, LReLU), (3×3)×32×32 convolution layer (step size 1, no padding, BN , LReLU), (3×3)×32×32 convolution layer (step size 1, no padding, BN, LReLU), (3×3)×32×32 convolution layer (step size 1, No padding, BN, LReLU), (3×3)×32×32 convolutional layer (stride 1, no padding, BN, LReLU), (3×3)×32×32 convolutional layer (step Length is 1, no padding, BN, LReLU), (1×1)×32×3 convolutional layer (step size is 1, no padding), the network structure is shown in Table 3.

[0155] table 3

[0156]

[0157]

[0158] Such as Figure 5 As shown, an underwater image enhancement method based on s...

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Abstract

The invention relates to an underwater image enhancement method and system based on structure decomposition, and a storage medium, and relates to the technical field of image enhancement, and the method comprises the steps: obtaining an original first underwater image; decomposing the original first underwater image into first high-frequency information HFI and first low-frequency information LFI; wherein the trained UWCNN-SD network model comprises a preliminary enhanced network model, and the preliminary enhanced network model comprises an LF enhanced network model and an HF enhanced network model; inputting the first high-frequency information HFI into the trained HF enhanced network model to obtain enhanced first enhanced high-frequency information, and inputting the first low-frequency information LFI into the trained LF enhanced network model to obtain enhanced first enhanced low-frequency information; and adding the enhanced first enhanced high-frequency information and the enhanced first enhanced low-frequency information at a pixel level to obtain a preliminarily enhanced first enhanced underwater image. According to the invention, the underwater image with higher visual quality and clearer texture details can be obtained.

Description

technical field [0001] The present application relates to the technical field of image enhancement, in particular to an underwater image enhancement method, system and storage medium based on structural decomposition. Background technique [0002] In recent years, the fields of underwater environment monitoring, marine resource development and marine military have flourished. However, original underwater images cannot meet the needs of vision tasks due to problems such as color distortion, blurring, and insufficient contrast. Therefore, underwater imaging technology has received extensive attention and research at home and abroad, and has been applied to various human underwater activities. For example, underwater activities such as underwater autonomous vehicles, underwater object capture, deep-sea exploration, and seabed mapping all rely heavily on high-definition, high-quality underwater images. [0003] Due to the complex underwater environment, the captured underwater...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06N3/04G06N3/08
Inventor 骆挺吴圣聪徐海勇宋洋
Owner COLLEGE OF SCI & TECH NINGBO UNIV