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Image-visibility-improving-master

于 2018-03-28 发布 文件大小:16931KB
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  去散射和边缘增强是水下图像从严重细节损失、颜色偏移和模糊中提取的关键步骤。本文提出了一种增强水下图像对比度和边缘的新方法。(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.)

文件列表：

Image-visibility-improving-master, 0 , 2018-03-08
Image-visibility-improving-master\Images, 0 , 2018-03-08
Image-visibility-improving-master\Images\101.jpg, 17096 , 2018-03-08
Image-visibility-improving-master\La1_4.jpg, 2197 , 2018-03-08
Image-visibility-improving-master\La1_5.jpg, 1729 , 2018-03-08
Image-visibility-improving-master\La2_1.jpg, 60612 , 2018-03-08
Image-visibility-improving-master\La2_2.jpg, 14638 , 2018-03-08
Image-visibility-improving-master\La2_3.jpg, 4103 , 2018-03-08
Image-visibility-improving-master\La2_4.jpg, 1370 , 2018-03-08
Image-visibility-improving-master\La3_1.jpg, 20493 , 2018-03-08
Image-visibility-improving-master\La3_2.jpg, 7439 , 2018-03-08
Image-visibility-improving-master\La3_3.jpg, 3587 , 2018-03-08
Image-visibility-improving-master\La3_4.jpg, 1756 , 2018-03-08
Image-visibility-improving-master\La3_5.jpg, 1231 , 2018-03-08
Image-visibility-improving-master\README.md, 773 , 2018-03-08
Image-visibility-improving-master\_config.yml, 28 , 2018-03-08
Image-visibility-improving-master\codes, 0 , 2018-03-08
Image-visibility-improving-master\codes\ColorHistogramEqulization.m, 951 , 2018-03-08
Image-visibility-improving-master\codes\DEHANZENET.m, 145 , 2018-03-08
Image-visibility-improving-master\codes\MyHistogramEqulization.m, 1170 , 2018-03-08
Image-visibility-improving-master\codes\RealGWbal.m, 637 , 2018-03-08
Image-visibility-improving-master\codes\SimplestColorBalance.m, 1749 , 2018-03-08
Image-visibility-improving-master\codes\UICM.m, 777 , 2018-03-08
Image-visibility-improving-master\codes\UIConM.m, 1881 , 2018-03-08
Image-visibility-improving-master\codes\UIQM.m, 207 , 2018-03-08
Image-visibility-improving-master\codes\UISM.m, 2130 , 2018-03-08
Image-visibility-improving-master\codes\autolevel.m, 2027 , 2018-03-08
Image-visibility-improving-master\codes\bfilter2.m, 1115 , 2018-03-08
Image-visibility-improving-master\codes\bfltColor.m, 1354 , 2018-03-08
Image-visibility-improving-master\codes\bfltGray.m, 1240 , 2018-03-08
Image-visibility-improving-master\codes\bilateralFilter.m, 6703 , 2018-03-08
Image-visibility-improving-master\codes\bilateral_filter.m, 1145 , 2018-03-08
Image-visibility-improving-master\codes\boxfilter.m, 929 , 2018-03-08
Image-visibility-improving-master\codes\convConst.mexw64, 29184 , 2018-03-08
Image-visibility-improving-master\codes\convMax.m, 2318 , 2018-03-08
Image-visibility-improving-master\codes\convolution.m, 772 , 2018-03-08
Image-visibility-improving-master\codes\dark_channelnew.m, 3869 , 2018-03-08
Image-visibility-improving-master\codes\darktest.m, 1291 , 2018-03-08
Image-visibility-improving-master\codes\dehaze.m, 700 , 2018-03-08
Image-visibility-improving-master\codes\dehaze.mat, 31902 , 2018-03-08
Image-visibility-improving-master\codes\dehaze_fast.m, 1266 , 2018-03-08
Image-visibility-improving-master\codes\expand.m, 755 , 2018-03-08
Image-visibility-improving-master\codes\gaussian_pyramid.m, 283 , 2018-03-08
Image-visibility-improving-master\codes\get_atmosphere.m, 445 , 2018-03-08
Image-visibility-improving-master\codes\get_dark_channel.m, 585 , 2018-03-08
Image-visibility-improving-master\codes\get_laplacian.m, 1665 , 2018-03-08
Image-visibility-improving-master\codes\get_radiance.m, 300 , 2018-03-08
Image-visibility-improving-master\codes\get_transmission_estimate.m, 256 , 2018-03-08
Image-visibility-improving-master\codes\guided_filter.m, 649 , 2018-03-08
Image-visibility-improving-master\codes\guidedfilter.m, 1020 , 2018-03-08
Image-visibility-improving-master\codes\hpfilter.m, 736 , 2018-03-08
Image-visibility-improving-master\codes\image2avi.m, 783 , 2018-03-08
Image-visibility-improving-master\codes\lab_to_rgb.m, 90 , 2018-03-08
Image-visibility-improving-master\codes\laplacia_conbine.m, 2522 , 2018-03-08
Image-visibility-improving-master\codes\laplacian_pyramid.m, 395 , 2018-03-08
Image-visibility-improving-master\codes\load_image.m, 158 , 2018-03-08
Image-visibility-improving-master\codes\main_of_la.m, 741 , 2018-03-08
Image-visibility-improving-master\codes\main_test_diff_weights.m, 3028 , 2018-03-08
Image-visibility-improving-master\codes\main_using_optimized.m, 2811 , 2018-03-08
Image-visibility-improving-master\codes\maxfilt2.m, 1784 , 2018-03-08
Image-visibility-improving-master\codes\pyramid_reconstruct.m, 308 , 2018-03-08
Image-visibility-improving-master\codes\rgb_to_lab.m, 90 , 2018-03-08
Image-visibility-improving-master\codes\run_cnn.m, 1681 , 2018-03-08
Image-visibility-improving-master\codes\saliency_detection.m, 2484 , 2018-03-08
Image-visibility-improving-master\codes\sse.hpp, 3125 , 2018-03-08
Image-visibility-improving-master\codes\ssim.m, 4430 , 2018-03-08
Image-visibility-improving-master\codes\ssim_score.m, 93 , 2018-03-08
Image-visibility-improving-master\codes\underwater.p, 1319 , 2018-03-08
Image-visibility-improving-master\codes\underwaterimage2.p, 963 , 2018-03-08
Image-visibility-improving-master\codes\vanherk.m, 4665 , 2018-03-08
Image-visibility-improving-master\codes\white_balance.p, 650 , 2018-03-08
Image-visibility-improving-master\codes\window_sum_filter.m, 608 , 2018-03-08
Image-visibility-improving-master\demo.m, 216 , 2018-03-08
Image-visibility-improving-master\result, 0 , 2018-03-08
Image-visibility-improving-master\result\La1_1.jpg, 24245 , 2018-03-08
Image-visibility-improving-master\result\La1_2.jpg, 8731 , 2018-03-08
Image-visibility-improving-master\result\La1_3.jpg, 4172 , 2018-03-08
Image-visibility-improving-master\result\La1_4.jpg, 2197 , 2018-03-08
Image-visibility-improving-master\result\La1_5.jpg, 1729 , 2018-03-08
Image-visibility-improving-master\result\La2_1.jpg, 60612 , 2018-03-08
Image-visibility-improving-master\result\La2_2.jpg, 14638 , 2018-03-08
Image-visibility-improving-master\result\La2_3.jpg, 4103 , 2018-03-08
Image-visibility-improving-master\result\La2_4.jpg, 1370 , 2018-03-08
Image-visibility-improving-master\result\La3_1.jpg, 20493 , 2018-03-08
Image-visibility-improving-master\result\La3_2.jpg, 7439 , 2018-03-08
Image-visibility-improving-master\result\La3_3.jpg, 3587 , 2018-03-08
Image-visibility-improving-master\result\La3_4.jpg, 1756 , 2018-03-08
Image-visibility-improving-master\result\La3_5.jpg, 1231 , 2018-03-08
Image-visibility-improving-master\result\We1_1.jpg, 102178 , 2018-03-08
Image-visibility-improving-master\result\We1_2.jpg, 31066 , 2018-03-08
Image-visibility-improving-master\result\We1_3.jpg, 9017 , 2018-03-08
Image-visibility-improving-master\result\We1_4.jpg, 3048 , 2018-03-08
Image-visibility-improving-master\result\We1_5.jpg, 1160 , 2018-03-08
Image-visibility-improving-master\result\result1.jpg, 82196 , 2018-03-08
Image-visibility-improving-master\result\result2.jpg, 99886 , 2018-03-08
Image-visibility-improving-master\result\result3.jpg, 73799 , 2018-03-08
Image-visibility-improving-master\result\result4.jpg, 102836 , 2018-03-08
Image-visibility-improving-master\水下图像清晰化.avi, 16909742 , 2018-03-08

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    《基于计算机视觉的普适性三维重建方法研究》源代码，实现了一种将二维图像重建成三维场景的方法。(Source code of <General Sense Three-Dimension Reconstruction Research Based on Computer Vision>, a technique which can convert 2D images into 3D sence.)
    2020-11-30 10:59:28下载
    积分：1
  • siftDemoV4
    SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。[1] 该方法于1999年由David Lowe[2] 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV）。截止2014年8月，该论文单篇被引次数达25000余次。(SIFT, namely Scale Invariant Feature Transform (Scale-invariant feature transform, SIFT), it is a description for image processing. This description has scale invariance, can detect critical point in the image, it is a local feature descriptor. [1] The method in 1999 by David Lowe [2] First published in the International Conference on Computer Vision (International Conference on Computer Vision, ICCV), 2004 was again perfect finishing after David Lowe published in the International journal of computer vision (IJCV) . As of August 2014, the paper cited the number of times a single article of more than 25,000 times.)
    2020-07-15 20:18:51下载
    积分：1
  • process_kang
    基于颜色的图像检索，将RGB转化成ＨＳＶ的方法(Color-based image retrieval, the method of RGB into HSV)
    2011-02-09 14:24:04下载
    积分：1
  • GPSDREKF
    目标运动的真实轨迹和估计轨迹，以及所进行的误差分析(Target motion trajectory and estimate the true trajectory, and error analysis conducted)
    2013-09-26 15:23:11下载
    积分：1
  • xingtaihexiaobo
    基于小波和形态学的自然地面背景红外目标检测方法。。。。。。(Based on wavelet and morphology of the natural terrestrial background infrared target detection method)
    2021-02-23 10:49:41下载
    积分：1
  • DIP_1
    The focus of this project is to experiment with intensity transformations to enhance an image.
    2008-12-26 23:29:13下载
    积分：1
  • 马尔科夫随机场算法matlab实现图像分辨率增强
    说明：  马尔科夫随机场算法matlab实现图像分辨率增强(Markov enhanced the image resolution)
    2020-03-19 20:19:25下载
    积分：1
  • 视差图完整
    说明：  对双目视觉处理的图像通过获取相机的内外参数后得出视差图，而后方便得到深度图等(The binocular vision processing image is obtained by obtaining the camera's internal and external parameters, and then the disparity map is obtained, and then the depth map is obtained.)
    2018-04-16 16:15:12下载
    积分：1
  • 源程序
    利用hough变换检测圆，有RHT，随机hough变换，以及一些改进(Using Hough transform to detect the circle)
    2018-04-22 18:08:35下载
    积分：1
  • target
    MATLAB编写的角点检测程序，用于对目标的检测和稳定的跟踪。很适合对于运动目标的精确跟踪。(Corner detection procedures written in MATLAB for target detection and tracking. Very suitable for the accurate tracking of moving targets.)
    2012-07-04 18:17:55下载
    积分：1
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