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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

  • texture-classification-with-lbp
    多分辨率灰度和旋转不变纹理分类与定位二进制模式(multiresolution gray scale and rotation invariant texture classification with location binary patterns )
    2014-02-25 16:45:10下载
    积分：1
  • luifunpui
    考虑雨衰 阴影 和多径影响，可直接计算得到多重分形谱,非归零型差分相位调制信号建模与仿真分析 。( Consider shadow rain attenuation and multipath effects It can be directly calculated multi-fractal spectrum, NRZ type differential phase modulation signal modeling and simulation analysis.)
    2017-05-29 12:04:39下载
    积分：1
  • MATLAB
    说明：  基于自组织神经网络数据及图像处理，在图像分割中应用极强。很好的源程序。 (Self-organizing neural network-based data and image processing, image segmentation in the application of highly. Very good source.)
    2008-10-20 15:23:57下载
    积分：1
  • featurepoints
    基于sift特征点的图像复制粘贴篡改被动认证(sift feature points copy-move forgery detction)
    2014-08-18 20:57:59下载
    积分：1
  • hhxrg
    高效的文章分句算法程序,将由标点符号分开的语句的起始位置和结束位置记录到结构体里()
    2017-12-09 07:42:10下载
    积分：1
  • guidedfilter
    引导滤波器，在引导图像的引导下对输入图像进行滤波，这种新型滤波器对边缘的保持很好，而且运行计算量和核的大小无关(Guide filters, under the guidance of the guide image filtering the input image, the edge of this new type of filter to keep well and run the calculation regardless of the size and nuclear)
    2011-10-21 15:21:43下载
    积分：1
  • popescu_resample
    基于预测误差周期性的图像重采样检测程序。(Image resampling detection based on the periodicity of prediction error)
    2020-08-12 11:28:26下载
    积分：1
  • MRF-grubcut
    通过Markov随机场（MRF）实现图像的分割，例程给出了图像分割为3类的MRF算法(By Markov random field (MRF) for image segmentation, image segmentation routine gives the MRF algorithm for the three classes)
    2013-08-26 21:48:28下载
    积分：1
  • GISA
    提出了一种广义迭代收缩算法（GISA）非凸稀疏编码，可以解决稀疏编码的一些优化问题.希望能对大家有所帮助！(A generalized iterative contraction algorithm (GISA) is proposed to solve some of the optimization problems of sparse coding. We hope to be helpful to everyone!)
    2017-04-24 11:42:26下载
    积分：1
  • Local
    说明：  用于虹膜图像处理过程中的定位过程，采用二值化结合hough变化方法进行虹膜区域的定位(For the iris image processing positioning process, combined with the use of binarization methods hough change the positioning of the iris region)
    2008-11-12 10:57:39下载
    积分：1
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