登录
首页 » matlab » ScSR

ScSR

于 2020-11-24 发布 文件大小:26991KB
0 196
下载积分: 1 下载次数: 457

代码说明:

  Jianchao Yang 的基于稀疏表示的单幅图像重建的原始代码,先将高低训练图像分块,再将块训练成高低字典,将测试图像映射到低字典上,得到系数,再乘以高子典就得到最后的图像。对学习超分辨率同学的参考作用很大。(This is the original matlab code for super resolution by Jianchao Yang 。The method is sparse represent based on the overcomplete dictionary。)

文件列表:

ScSR
....\backprojection.m,460,2011-01-28
....\compute_rmse.m,293,2011-01-12
....\Data
....\....\Testing



....\....\Training





....\....\........\t16.bmp,83894,2007-10-14
....\....\........\t17.bmp,69786,2007-10-14
....\....\........\t18.bmp,55782,2007-10-14
....\....\........\t19.bmp,96174,2007-10-14
....\....\........\t2.bmp,92418,2007-10-14
....\....\........\t20.bmp,18462,2007-10-14
....\....\........\t21.bmp,41346,2007-10-14
....\....\........\t22.bmp,59718,2007-10-14
....\....\........\t23.bmp,46902,2007-10-14
....\....\........\t24.bmp,37290,2007-10-14
....\....\........\t25.bmp,125190,2007-10-14
....\....\........\t26.bmp,58742,2007-10-14
....\....\........\t27.bmp,126030,2007-10-14
....\....\........\t28.bmp,92550,2007-10-14
....\....\........\t3.bmp,89334,2007-10-14
....\....\........\t30.bmp,61662,2007-10-14
....\....\........\t31.bmp,101670,2007-11-09
....\....\........\t32.bmp,86646,2007-11-09
....\....\........\t34.bmp,66362,2007-11-09
....\....\........\t35.bmp,125306,2007-11-09
....\....\........\t36.bmp,114102,2007-11-23
....\....\........\t37.bmp,312390,2007-11-22
....\....\........\t38.bmp,200054,2007-11-22
....\....\........\t39.bmp,197350,2007-11-22
....\....\........\t4.bmp,128646,2007-10-14
....\....\........\t40.bmp,200082,2007-11-22
....\....\........\t42.bmp,202814,2007-11-23
....\....\........\t43.bmp,157134,2007-11-23
....\....\........\t44.bmp,115722,2007-11-23
....\....\........\t46.bmp,355146,2007-11-22
....\....\........\t47.bmp,143574,2007-11-22
....\....\........\t48.bmp,135462,2007-11-22
....\....\........\t49.bmp,243022,2007-11-22
....\....\........\t5.bmp,70734,2007-10-14
....\....\........\t50.bmp,259958,2007-11-22
....\....\........\t51.bmp,251910,2007-11-22
....\....\........\t52.bmp,207090,2007-11-22
....\....\........\t59.bmp,214134,2007-11-23
....\....\........\t6.bmp,90102,2007-10-14
....\....\........\t60.bmp,141394,2007-11-23
....\....\........\t61.bmp,111254,2007-11-23
....\....\........\t62.bmp,118194,2007-11-23
....\....\........\t63.bmp,148726,2007-11-23
....\....\........\t66.bmp,234090,2007-11-22
....\....\........\t7.bmp,83898,2007-10-14
....\....\........\tt1.bmp,407454,2009-05-21
....\....\........\tt12.bmp,343350,2009-05-21
....\....\........\tt14.bmp,153462,2009-05-21
....\....\........\tt15.bmp,216534,2009-05-21
....\....\........\tt17.bmp,238878,2009-05-21
....\....\........\tt18.bmp,95898,2009-05-21
....\....\........\tt19.bmp,190454,2009-05-21
....\....\........\tt2.bmp,459162,2009-05-21
....\....\........\tt20.bmp,266442,2009-05-21
....\....\........\tt21.bmp,383214,2009-05-21
....\....\........\tt24.bmp,339414,2009-05-21
....\....\........\tt25.bmp,414774,2009-05-21
....\....\........\tt26.bmp,358494,2009-05-21
....\....\........\tt27.bmp,283722,2009-05-21
....\....\........\tt3.bmp,455238,2009-05-21
....\....\........\tt4.bmp,427302,2009-05-21
....\....\........\tt5.bmp,406314,2009-05-21
....\....\........\tt7.bmp,142922,2009-05-21
....\....\........\tt9.bmp,436926,2009-05-21
....\Demo_Dictionary_Training.m,1437,2011-03-07
....\Demo_SR.m,2399,2011-03-07
....\Dictionary
....\..........\D_1024_0.15_5.mat,983828,2011-01-04
....\..........\D_512_0.15_5.mat,492077,2011-01-04
....\extr_lIm_fea.m,433,2011-01-28
....\L1QP_FeatureSign_yang.m,1608,2009-09-30
....\lin_scale.m,128,2011-03-04
....\patch_pruning.m,144,2011-03-07
....\Previous
....\........\ScSR.rar,12388885,2009-05-31
....\........\SR-Results.rar,3172715,2009-04-08
....\README.dat,1483,2011-10-30
....\RegularizedSC
....\.............\construct_reg_mat.m,394,2009-09-25
....\.............\display_network_nonsquare2.m,965,2009-03-05
....\.............\getObjective_RegSc.m,306,2009-09-24
....\.............\L1QP_FeatureSign_Set.m,331,2010-01-30
....\.............\L1QP_FeatureSign_yang.m,1608,2009-09-30
....\.............\l2ls_learn_basis_dual.m,2371,2009-03-05
....\.............\regsc.m,362,2009-09-25
....\.............\reg_sparse_coding.m,3307,2010-12-24

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • PCA
    图像超分辨率重建算法,实现图像的超分辨率重建。(super-resolution code )
    2011-01-06 12:33:50下载
    积分:1
  • jpeg_quality_score
    基于JPEG压缩的无参考图像质量评价算法,输入一幅图像,输出图像的评价值,值在0-100之间,越接近0图像的质量越好(JPEG-based compression algorithm for no-reference image quality assessment, an input image, the output image uation value, a value between 0-100, closer to 0 the better the image quality)
    2014-11-27 14:12:41下载
    积分:1
  • Image_Steg
    Image Steganograpy using Pixel-Value Differencing
    2012-10-10 16:39:03下载
    积分:1
  • GUI
    说明:  首先对指纹图像进行预处理,包括图像的分割,增强,二值化,细化。对细化后的图像进行特征点的提取,最后通过细节特征匹配完成指纹的识别。(Firstly, the fingerprint image is preprocessed, including image segmentation, enhancement, binarization and thinning. The refined image is extracted by feature points, and the fingerprint recognition is completed by minutiae feature matching.)
    2019-05-07 13:46:08下载
    积分:1
  • plotgdop
    代码主要用来模拟林芝机场附近一天内4个不同时间GDOP变化情况(Code is mainly used to simulate the Nyingchi Airport near four different times within a day GDOP changes)
    2013-08-05 09:51:15下载
    积分:1
  • GM
    说明:  残差灰色模型的改进算法。可以得到高精确度的预测,很实用,并附有测试文件(Improved algorithm for gray model residuals. Can be predicted with high accuracy, very practical, with a test file)
    2011-06-04 22:20:10下载
    积分:1
  • kld
    基于数学形态学的图像颗粒度分析算法,先去噪再求面积然后绘制颗粒度函数。(based on mathematical morphology particle size analysis algorithms, first try to de-noising area before drawing particles function.)
    2006-06-24 13:10:11下载
    积分:1
  • fingertips
    利用OpenCV实现单幅图片对于手指的精确识别(Single image using OpenCV to achieve precise identification of the finger)
    2011-02-11 17:09:05下载
    积分:1
  • Kmeans
    说明:  基于Kmeans算法的图像分割,一般Kmeans是数据挖掘中用来聚类的,本试验利用图像中的灰度值作为Kmeans算法的原始点,进行图像分割(Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for Image Segmentation)
    2021-04-06 16:49:03下载
    积分:1
  • quzao
    对比了常见的几种去噪方法,含中值滤波,均值滤波,维纳滤波,高斯滤波,以及三种形态学滤波(一般的,改进的,多结构元素形态学滤波)(Comparison of several common Denoising containing median filtering, mean filtering, Wiener filtering, Gaussian filtering, as well as three morphological filtering (generally improved, multi-structural elements morphological filtering))
    2013-04-10 10:10:18下载
    积分:1
  • 696518资源总数
  • 106164会员总数
  • 18今日下载