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于 2010-11-13 发布文件大小:181KB

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下载积分: 1 下载次数: 211

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代码说明：

本代码用matlab实现了图像的Jpeg编解码，使我的毕业设计，在这里与大家共享。(The code is implemented using matlab Jpeg image codec, so my graduation, and share here.)

文件列表：

4
.\AcCode.m,964,2009-09-21
.\cate.m,52,2009-09-20
.\code.asv,874,2009-09-26
.\code.m,941,2009-09-26
.\code.mat,261,2009-09-26
.\czigzag.m,587,2009-09-18
.\DcCode.m,491,2009-09-21
.\decipher.mat,323,2009-09-26

.\decode.m,3286,2009-09-22
.\evaluate.m,198,2009-09-22
.\getbin.m,202,2009-09-18
.\getnum.m,281,2009-09-17
.\hall.mat,75386,2009-09-03
.\hall_code.mat,19120,2009-09-22
.\hall_decode.mat,18354,2009-09-26
.\hall_gray.mat,18895,2009-09-22
.\hall_new.mat,18357,2009-09-22
.\jpegcodes.mat,4555,2009-09-26
.\JpegCoeff.mat,668,2009-09-18
.\main.m,207,2009-09-22
.\mydct.m,267,2009-09-20
.\myidct.m,266,2009-09-20

.\zigzag.m,439,2009-09-17

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卡尔曼滤波源代码 Some brief notes ---------------- kfdemo.m is a Matlab script file to run a demonstration of the Bayesian Kalman filter. It loads file kfdemo.mat (saved as version 4 so that it will read in either v4 or v5 Matlab). The other files are called by kf.m (the Kalman filter) or included as they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any further analysis. Steve Roberts 7-2-98 (Kalman filter source code Some brief notes kfdemo.m is a Matlab script file to run a demonstration of theBayesian Kalman filter. It loads file kfdemo.mat (saved as version 4so that it will read in either v4 or v5 Matlab). The other files are called by kf.m (the Kalman filter) or includedas they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any furtheranalysis.Steve Roberts 7-2-98)

2008-04-05 16:47:47下载

积分：1
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2012-08-02 21:35:43下载

积分：1
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摘　要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。(Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2 ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2 pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3 b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack.)

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积分：1
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提出了一种基于非下采样Contourlet 变换的自适应图像去噪方法首先对噪声图像进行非下采样Contourlet 变换，得到各个尺度各个方向子带的系数，再根据该系数的能量自适应地调整去噪阈值实验表明，与Contourlet 多尺度阈值去噪 Contourlet 自适应阈值去噪相比，该方法在保留图像边缘细节的同时，能提高图像的PSNR 值，减少了Gibbs 现象(A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform （NSCT）is presented.Firstly， the noisy image is decomposed into a set of multiscale and multidirectional frequency subbands by NSCT， and then the threshold is adapted automatically according to the energy of subband coefficients.Compared with the multi-scale threshold using contourlet transform and using adaptive threshold based on contourlet transform， the simulation results show that the performance of this method is superior in PSNR， meanwhile it can maintain the image edge and reduce the Gibbs phenomen)

2012-07-20 10:49:25下载

积分：1
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2012-04-23 20:54:52下载

积分：1
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积分：1
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SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点，其匹配能力较强，可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题，甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力。该算法目前外文资料较多，但中文方面的介绍较少.(SIFT feature matching algorithm is at home and abroad feature points matching hot area of research and difficulties in its matching capability that can handle between the two images, translation, rotation, the matching problem in the case of affine transformation, and even to some extent have a relatively stable feature of the ability to match images taken on any angle. The algorithm is more foreign materials, but the Chinese introduction less.)

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积分：1
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