基于卷积神经网络的水下图像增强方法

doi:10.13229/j.cnki.jdxbgxb20170815

Abstract

Abstract:

In order to avoid the problems of manually selecting features, difficulties in feature extraction and low visibility in traditional underwater image enhancing methods, an underwater image enhancing method based on convolution neural network was proposed. First, an underwater image dataset was established by simulation of underwater image formatting process by using clear images and underwater degraded model. Then, a convolution neural network model for underwater image enhancement was established, which can directly create a mapping relationship between the clear image and the underwater image. Finally, underwater images were restored by the features extracted by convolution neural network of underwater image. The experimental results show that the proposed method has less noise and improves contrast than tradition methods, and the algorithm provides a new idea for the underwater image enhancing research.

Key words: information procession technology, convolutional neural network, underwater images, image enhancing, visibility

CLC Number:

TP391.4

XU Yan,SUN Mei-shuang. Enhancing underwater image based on convolutional neural networks[J].Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1895-1903.

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试验编号	第1层卷积核尺寸	第2层卷积核尺寸	第3层卷积核尺寸	第4层卷积核尺寸	平均PSNR/dB
1	7×7	5×5	5×5	3×3	26.363
2	5×5	5×5	5×5	3×3	26.181
3	5×5	5×5	3×3	3×3	26.121
4	3×3	3×3	3×3	3×3	26.080

层的名称	特征图个数	卷积核尺寸	特征图扩充尺寸	卷积核移动步长
1	64	7×7	2	1
2	32	5×5	2	1
3	16	5×5	2	1
4	3	3×3	2	1

指标	算法	图片
指标	算法	Teddy	Art	Reindeer	Aloe	Dolls
PSNR/dB	Fattal	10.134	11.759	13.001	10.012	10.681
	Fu	15.712	14.251	12.136	11.709	15.024
	Ancuti	14.891	11.971	10.484	16.094	12.946
	本文	25.926	25.104	25.585	26.801	26.599
RMSE	Fattal	8.639	7.687	7.039	8.839	8.209
	Fu	5.953	6.489	7.046	7.477	6.061
	Ancuti	6.179	7.274	7.851	5.771	6.778
	本文	3.804	3.058	3.141	2.909	3.048

算法	均值	标准差	信息熵	平均梯度
Fattal	98.4971	61.3326	6.8398	6.2389
Fu	135.9848	69.0856	7.0569	8.4456
Ancuti	144.8726	68.5824	7.7185	9.1866
本文	143.2409	69.2448	7.7712	9.5125

Enhancing underwater image based on convolutional neural networks

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