水下图像去雾与增强
所属分类：图形图象
开发工具：matlab
文件大小：37093KB
下载次数：111
上传日期：2019-06-01 09:11:45
上 传 者：
凫枭
说明： 这篇论文提出了一种较好的水下图像增强的方法。首先使用经过端到端训练的卷积神经网络去测量输入图片，同时以自适应双边滤波器对传输图片进行处理。接着提出一种基于白平衡的策略来消除图片的颜色偏差，用拉普拉斯金字塔融合获得无雾和色彩校正图像的融合结果。 最后，输出图像被转换为混合小波和方向滤波器组（HWD）域，用于去噪和边缘增强。 实验结果表明，该方法可以消除颜色失真，提高水下图像的清晰度。
(This paper proposes a better underwater image enhancement method. Firstly, an end-to-end training convolutional neural network is used to measure the input image, and an adaptive bilateral filter is used to process the transmitted image. Then a strategy based on white balance is proposed to eliminate the color deviation of images. The fusion results of fog-free and color correction images are obtained by Laplacian pyramid fusion. Finally, the output image is converted into hybrid wavelet and directional filter bank (HWD) domain for denoising and edge enhancement. The experimental results show that the method can eliminate color distortion and improve the clarity of underwater images.)
文件列表:
codes\autolevel.m (2027, 2019-03-09)
codes\bfilter2.m (1115, 2019-03-09)
codes\bfltColor.m (1354, 2019-03-09)
codes\bfltGray.m (1240, 2019-03-09)
codes\bilateralFilter.m (6703, 2019-03-09)
codes\bilateral_filter.m (1145, 2019-03-09)
codes\boxfilter.m (929, 2019-03-09)
codes\ColorHistogramEqulization.m (951, 2019-03-09)
codes\convConst.mexw64 (29184, 2019-03-09)
codes\convMax.m (2318, 2019-03-09)
codes\convolution.m (772, 2019-03-09)
codes\darktest.m (1291, 2019-03-09)
codes\dark_channelnew.m (3869, 2019-03-09)
codes\DEHANZENET.m (145, 2019-03-09)
codes\dehaze.m (700, 2019-03-09)
codes\dehaze.mat (31902, 2019-03-09)
codes\dehaze_fast.m (1266, 2019-03-09)
codes\expand.m (755, 2019-03-09)
codes\gaussian_pyramid.m (283, 2019-03-09)
codes\get_atmosphere.m (445, 2019-03-09)
codes\get_dark_channel.m (585, 2019-03-09)
codes\get_laplacian.m (1665, 2019-03-09)
codes\get_radiance.m (300, 2019-03-09)
codes\get_transmission_estimate.m (256, 2019-03-09)
codes\guidedfilter.m (1020, 2019-03-09)
codes\guided_filter.m (649, 2019-03-09)
codes\hpfilter.m (736, 2019-03-09)
codes\image2avi.m (783, 2019-03-09)
codes\image_dehazing.m (1254, 2019-03-23)
codes\lab_to_rgb.m (90, 2019-03-09)
codes\laplacian_pyramid.m (395, 2019-03-09)
codes\laplacia_conbine.m (2522, 2019-03-09)
codes\load_image.m (158, 2019-03-09)
codes\main_of_la.m (741, 2019-03-09)
codes\main_test_diff_weights.m (3028, 2019-03-09)
codes\main_using_optimized.m (2811, 2019-03-09)
codes\maxfilt2.m (1784, 2019-03-09)
codes\MyHistogramEqulization.m (1170, 2019-03-09)
codes\pyramid_reconstruct.m (308, 2019-03-09)
codes\RealGWbal.m (637, 2019-03-09)
... ...
Image visibility improving
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Reference:
Pan-wang Pan, Fei Yuan, and En Cheng, UNDERWATER IMAGE DE-SCATTERING AND ENHANCING USING DEHAZENET AND HWD, Journal of Marine Science and Technology[J], Vol. 26, No. 4, pp. 531-540 (2018)
DOI: 10.6119/JMST.201808_26(4).0006
De-scattering and edge enhancing are critical procedures for underwater images which surfer from serious detail loss, color deviation and blurring. In this work, a novel method has been proposed to enhance contrast and edge of underwater images.
How to use?
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Run demo.m
Results
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