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3D-IQA-master

于 2019-11-23 发布
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代码说明：

说明：  关于立体图像质量评价的论文和一些工程实现代码。(Papers on stereo image quality evaluation and some engineering implementation code.)

文件列表：

3D-IQA-master\Experiment\divine_feature_extract.m, 2425 , 2017-06-30
3D-IQA-master\Experiment\edge.m, 874 , 2017-06-30
3D-IQA-master\Experiment\mj_stereo_SSIM.m, 5025 , 2017-06-30
3D-IQA-master\Experiment\qilv.m, 2309 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\example.m, 166 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\feature_extract.m, 861 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\fecal.m, 169 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\secal.m, 51 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\setscale.m, 160 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\SSEQ.m, 119 , 2017-06-30
3D-IQA-master\Experiment\SSEQ\SSQA_by_f.m, 354 , 2017-06-30
3D-IQA-master\Experiment\wavelet\fusion.m, 738 , 2017-06-30
3D-IQA-master\Experiment\wavelet\saliency_SR.m, 828 , 2017-06-30
3D-IQA-master\Experiment\wavelet\wavelet.m, 1902 , 2017-06-30
3D-IQA-master\Experiment\wavelet\wavelet1.m, 2969 , 2017-06-30
3D-IQA-master\Experiment\wavelet\wavelet2.m, 1337 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\ExtractGaborResponse.m, 1631 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\MJ3DQA.m, 2527 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\mj_computeDispCompIm.m, 531 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\mj_GenMergeWEntropy.m, 505 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\mj_stereo_SSIM.m, 5025 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\msssim.m, 2319 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\ssim.m, 6372 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\ssim_index_new.m, 2439 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR\test_live_phase.m, 2169 , 2017-06-30
3D-IQA-master\FR-3D-IQA\Stereoscopic Image Quality Assessment by Analyzing Depth and Local Texture Information.pdf, 387136 , 2017-06-30
3D-IQA-master\NR-3D-IQA\analysisLIVE3D1.m, 4719 , 2017-06-30
3D-IQA-master\NR-3D-IQA\analysisLIVE3D2.m, 5692 , 2017-06-30
3D-IQA-master\NR-3D-IQA\brisque_feature.m, 847 , 2017-06-30
3D-IQA-master\NR-3D-IQA\estimateggdparam.m, 689 , 2017-06-30
3D-IQA-master\NR-3D-IQA\feature_extract.m, 1174 , 2017-06-30
3D-IQA-master\NR-3D-IQA\findCorrelation.m, 458 , 2017-06-30
3D-IQA-master\NR-3D-IQA\logistic5.m, 119 , 2017-06-30
3D-IQA-master\NR-3D-IQA\mj_stereo_SSIM.m, 5025 , 2017-06-30
3D-IQA-master\NR-3D-IQA\No-reference Stereoscopic Image Quality Assessment with Saliency-guided Binocular Feature Consolidation.pdf, 407140 , 2017-06-30
3D-IQA-master\NR-3D-IQA\saliency_SR.m, 949 , 2017-06-30
3D-IQA-master\NR-3D-IQA\stereo_NR.m, 2601 , 2017-06-30
3D-IQA-master\NR-3D-IQA\VarInformation.m, 481 , 2017-06-30
3D-IQA-master\README.md, 673 , 2017-06-30
3D-IQA-master\Visual comfort assessment\compute_disparity.m, 1833 , 2017-06-30
3D-IQA-master\Visual comfort assessment\compute_edge.m, 1754 , 2017-06-30
3D-IQA-master\Visual comfort assessment\feature_extract3.m, 1188 , 2017-06-30
3D-IQA-master\Visual comfort assessment\FGr.m, 1146 , 2017-06-30
3D-IQA-master\Visual comfort assessment\frequency_domain.m, 1401 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\compute.m, 211 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\get4orient.m, 505 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\geteqdis.m, 289 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\getgbvsmap.m, 239 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\getmarkovtrans.m, 453 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\Gscale.m, 1306 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\myGBVS.m, 1410 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs\normgbvs.m, 461 , 2017-06-30
3D-IQA-master\Visual comfort assessment\README.md, 318 , 2017-06-30
3D-IQA-master\Visual comfort assessment\VISUAL COMFORT ASSESSMENT.pdf, 513391 , 2017-06-30
3D-IQA-master\Visual comfort assessment\visualComfort_feature.m, 1226 , 2017-06-30
3D-IQA-master\Visual comfort assessment\visual_stereo_NR.m, 1824 , 2017-06-30
3D-IQA-master\Experiment\SSEQ, 0 , 2017-06-30
3D-IQA-master\Experiment\wavelet, 0 , 2017-06-30
3D-IQA-master\FR-3D-IQA\code_for_FR, 0 , 2017-06-30
3D-IQA-master\Visual comfort assessment\gbvs, 0 , 2017-06-30
3D-IQA-master\Experiment, 0 , 2017-06-30
3D-IQA-master\FR-3D-IQA, 0 , 2017-06-30
3D-IQA-master\NR-3D-IQA, 0 , 2017-06-30
3D-IQA-master\Visual comfort assessment, 0 , 2017-06-30
3D-IQA-master, 0 , 2017-06-30

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发表评论

0 个回复

  • 图片裁剪
    快速将图片裁剪为电脑壁纸和ipad壁纸尺寸，带预览(To cut pictures as PC or Ipad size conveniently)
    2020-06-20 18:40:02下载
    积分：1
  • N_lms
    NLMS算法的仿真，用于对比LMS算法，描绘了平方误差和输出图形(The simulation of NLMS)
    2011-06-04 09:00:23下载
    积分：1
  • 5yc
    时空域下的信息隐藏技术，LSB ,MSB以及二值图像中的信息隐藏(When the airspace under the information hiding technology, LSB, MSB, as well as binary images of Information Hiding)
    2021-04-01 23:29:07下载
    积分：1
  • SobelKirsch
    模式识别的Sobel和Kirsch边缘检测程序(Sobel and Kirsch edge detection algorithm of Pattern recognition)
    2010-11-26 16:43:14下载
    积分：1
  • logisticmefan
    基于混沌的序列的对数字图像进行的魔方加密变换，介绍了非线性动力学系统的logistic映射形成的混沌序列的方法 。(Based on chaotic sequence of digital images of the Rubik)
    2007-10-14 10:59:49下载
    积分：1
  • lane-detect
    canny边缘检测，还有车道线检测。效果还可以。(canny edge detection, and lane detection. The effect can be.)
    2014-01-14 16:44:00下载
    积分：1
  • 压缩感知中利用增广拉格朗日方程解最小稀疏正则化的恢复算法 DAL
    压缩感知中利用增广拉格朗日方程解最小稀疏正则化的恢复算法(DAL solves the dual problem of (1) via the augmented Lagrangian method (see Bertsekas 82). It uses the analytic expression (and its derivatives) of the following soft-thresholding operation， which can be computed for L1 and grouped L1 (and many other) sparsity inducing regularizers. If you are interested in our algorithm please find more details in our technical report or in my talk at Optimization for Machine Learning Workshop (NIPS 2009).)
    2011-04-25 10:19:38下载
    积分：1
  • hough
    hough变换提取图像中圆的半径和圆心坐标(hough transform to extract the radius and center)
    2014-07-15 20:48:43下载
    积分：1
  • lankton_stereo
    一个外国人写的基于分割的立体匹配算法代码，可以在matlab7.1以后版本中直接执行，代码结构也很清晰，适合分析学习(Written by a foreigner based on the partition of the three-dimensional matching algorithm code, you can later matlab7.1 direct the implementation of the code structure is very clear and suitable for analysis of learning)
    2008-06-20 09:57:22下载
    积分：1
  • work
    针对FCM算法的运行时间长和计算量大的问题，提出了改进的FCM算法，先将图像分割成窗口大小的子块，然后以子块为单位提取特征向量，用FCM聚类粗分割，然后对边缘子块，以像素为单位从新提取特征向量，进行细分割。分割后的结果提高了运行速度和分割精度。(For the FCM algorithm and the calculation of long run the problem of large proposed improved FCM algorithm, first image into blocks the size of the window, and then sub-block feature vector extraction unit, using FCM clustering coarse partition, and then block on the edge, in pixels from the new Feature Extraction, for fine segmentation. Improve the segmentation results after the speed and accuracy of segmentation.)
    2011-06-06 20:51:45下载
    积分：1
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