登录
首页 » matlab » qtfm_2_0

qtfm_2_0

于 2013-10-18 发布 文件大小:770KB
0 235
下载积分: 1 下载次数: 149

代码说明:

  利用四元数对彩色图像进行各种图像处理的,如滤波、快速傅立叶变化、图像质量评价等。(Use quaternion various images for color image processing, such as filtering, fast Fourier transform, the image quality evaluation.)

文件列表:

qtfm
....\@octonion
....\.........\abs.m,487,2013-03-28
....\.........\cast.m,487,2013-03-28
....\.........\cd.m,443,2013-03-28
....\.........\char.m,3286,2013-03-28
....\.........\complex.m,644,2013-03-28
....\.........\conj.m,1414,2013-03-28
....\.........\cross.m,284,2013-03-28
....\.........\ctranspose.m,381,2013-03-28
....\.........\diag.m,455,2013-03-28
....\.........\disp.m,2132,2013-03-28
....\.........\display.m,1263,2013-03-28
....\.........\displayall.m,313,2013-03-28
....\.........\end.m,476,2013-03-28
....\.........\eq.m,1404,2013-03-28
....\.........\full.m,382,2013-03-28
....\.........\horzcat.m,1394,2013-03-28
....\.........\imag.m,492,2013-03-28
....\.........\inv.m,1012,2013-03-28
....\.........\isempty.m,344,2013-03-28
....\.........\isfinite.m,398,2013-03-28
....\.........\ispure.m,688,2013-03-28
....\.........\isreal.m,532,2013-03-28
....\.........\length.m,403,2013-03-28
....\.........\linv.m,2395,2013-03-28
....\.........\lu.m,3791,2013-04-02
....\.........\minus.m,390,2013-03-28
....\.........\mpower.m,760,2013-03-28
....\.........\mtimes.m,2832,2013-03-28
....\.........\ndims.m,432,2013-03-28
....\.........\ne.m,400,2013-03-28
....\.........\norm.m,1850,2013-04-02
....\.........\normo.m,357,2013-03-28
....\.........\numel.m,1364,2013-03-28
....\.........\octonion.m,7548,2013-03-28
....\.........\part.m,534,2013-03-28
....\.........\plus.m,2891,2013-03-28
....\.........\power.m,2841,2013-03-28
....\.........\private
....\.........\.......\component.m,594,2013-03-28
....\.........\.......\nu.m,1824,2013-03-28
....\.........\.......\omega.m,2297,2013-03-28
....\.........\.......\overload.m,801,2013-03-28
....\.........\.......\phi.m,1725,2013-03-28
....\.........\.......\show_internal.m,2887,2013-03-28
....\.........\.......\tao.m,1725,2013-03-28
....\.........\.......\unimplemented.m,353,2013-03-28
....\.........\rdivide.m,1287,2013-03-28
....\.........\real.m,438,2013-03-28
....\.........\rinv.m,2425,2013-03-28
....\.........\s.m,300,2013-03-28
....\.........\scalar.m,465,2013-03-28
....\.........\scalar_product.m,782,2013-03-28
....\.........\show.m,310,2013-03-28
....\.........\size.m,1659,2013-03-28
....\.........\subsasgn.m,2168,2013-03-28
....\.........\subsref.m,783,2013-03-28
....\.........\sum.m,1008,2013-03-28
....\.........\times.m,1523,2013-03-28
....\.........\transpose.m,364,2013-03-28
....\.........\tril.m,440,2013-03-28
....\.........\triu.m,441,2013-03-28
....\.........\uminus.m,359,2013-03-28
....\.........\unit.m,1795,2013-03-28
....\.........\uplus.m,381,2013-03-28
....\.........\v.m,366,2013-03-28
....\.........\vector.m,372,2013-03-28
....\.........\vector_product.m,1978,2013-03-28
....\.........\vertcat.m,1390,2013-03-28
....\@quaternion
....\...........\abs.m,637,2013-04-02
....\...........\acos.m,916,2009-02-08
....\...........\acosh.m,943,2009-02-08
....\...........\adjoint.m,9244,2013-04-02
....\...........\angle.m,5291,2013-04-02
....\...........\arrayfun.m,569,2009-12-23
....\...........\asin.m,912,2009-02-08
....\...........\asinh.m,939,2009-02-08
....\...........\atan.m,918,2009-02-08
....\...........\atanh.m,945,2009-02-08
....\...........\axis.m,1532,2013-04-02
....\...........\blkdiag.m,1785,2010-12-19
....\...........\bsxfun.m,2405,2010-05-13
....\...........\cast.m,490,2009-02-08
....\...........\cat.m,2320,2013-04-02
....\...........\cd.m,916,2009-02-08
....\...........\cdpolar.m,6595,2010-12-19
....\...........\ceil.m,378,2009-02-08
....\...........\change_basis.m,1851,2013-04-02
....\...........\char.m,2711,2013-04-02
....\...........\complex.m,650,2009-12-10
....\...........\conj.m,1179,2013-04-02
....\...........\conv.m,8847,2009-02-08
....\...........\conv2.m,7899,2013-03-26
....\...........\convert.m,925,2010-12-19
....\...........\cos.m,943,2013-04-02
....\...........\cosh.m,947,2013-04-02
....\...........\cross.m,272,2013-04-02
....\...........\ctranspose.m,773,2013-04-02

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

  • Estimation-master
    图像基本算法研究,具有一定的参考价值,供大家参考(Image basic algorithm research, has a certain reference value for your reference)
    2016-07-08 15:35:18下载
    积分:1
  • HMarkDemo
    基于Halcon开发的掩模 纯手工编辑(Mask editing based on Halcon)
    2020-07-02 20:00:02下载
    积分:1
  • dark_channel_new
    单幅图象的暗原色先验去雾改进算法,能够很好地改进天空或明亮部分色彩失真问题,matlab代码注解详细,能很好地帮助理解算法过程。(improvement of a single image dehazing algorithm using dark channel prior,solving the problem of color distortion of sky and bright part!Having a good explain of the code,which could be helpful to understand the processing of the algorithm! )
    2012-10-25 09:20:55下载
    积分:1
  • ICAforImage
    Matlab环境下的基于独立分量分析(ICA)算法的图像混合与分离仿真程序.(Matlab environment based on the independent component analysis (ICA) algorithm for image simulation mixed with the separation process sequence.)
    2020-11-23 12:29:35下载
    积分:1
  • EntropyRateSuperpixel-master
    基于熵率的超像素分割,图像处理,图像分割技术(superpixel segmentation based on entropy rate, image processing, image segmentation technology)
    2018-05-21 17:03:55下载
    积分:1
  • TIP_14_SPL
    基于多尺度超像素的显著性检测代码和文章(Saliency Detection with Multi-Scale Superpixels)
    2020-09-16 16:57:55下载
    积分:1
  • Saliency
    CVPR2013中出现的一种显著性特征检测算法,该算法用于模拟人眼视觉识别过程,提取图像中的显著性特征借后期目标对象的检测跟踪等使用,该算法(Context-Aware Saliency Detection。matlab implementation of an classical saliency detection alrogithm,which imitate our recognition process of eyes)
    2013-10-03 22:45:25下载
    积分:1
  • qa3
    生成静态散斑图,通过快速傅里叶变换,得到激光散斑图。(Generate static speckle pattern)
    2012-11-13 15:15:45下载
    积分:1
  • sfpxh3
    A fast matching algorithm based on image gray scale, in PDF format, good
    2017-05-07 11:10:28下载
    积分:1
  • 20064817924orl_faces_112x92
    说明:  ORL人脸图像库,共40人,每人10幅图像,其中每人的前5幅作为训练样本,后5幅作为测试分类样本,统计正确分类率。分类准则为最近邻规则。 真实的图像尺寸为112x92,列向量堆积对应人脸库矩阵的每一列。 (ORL face image database, a total of 40 per 10 images, each of which the first five as training samples, after the 5 categories as a test sample, correct classification rate statistics. Classification criteria for the nearest neighbor rule. The real image size is 112x92, the corresponding column vector face database matrix accumulation of each column.)
    2010-03-31 17:47:06下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载