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blind-deconvolution

于 2011-10-28 发布文件大小:16975KB

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代码说明：

包括一片英文文献及其所对应的代码实现，主要功能是实现对运动模糊图像的复原。(Including an English literature and its corresponding code, the main function is to achieve restoration of motion blurred images.)

文件列表：

fergus_2011blind deconvolution using a normalized sparsity measure
..................................................................\blinddeconv
..................................................................\...........\center_kernel_separate.m,988,2011-06-28
..................................................................\...........\fast_deconv_bregman.m,3169,2011-05-26

..................................................................\...........\lyndsey.tif,3957468,2011-05-26
..................................................................\...........\ms_blind_deconv.m,5929,2011-06-28

..................................................................\...........\pcg_kernel_core_irls_conv.m,448,2011-02-03
..................................................................\...........\pcg_kernel_irls_conv.m,2194,2011-05-26
..................................................................\...........\pietro.tif,1489716,2011-05-26
..................................................................\...........\README.txt,725,2011-06-28
..................................................................\...........\solve_image_bregman.m,6074,2011-01-30
..................................................................\...........\ss_blind_deconv.m,3385,2011-06-28
..................................................................\...........\test_blind_deconv.m,1862,2011-06-28
..................................................................\priors_cvpr11[1].pdf,14336400,2011-10-28

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wheel-treadmonitoring
城轨车辆轮对踏面故障在线监测系统，基于振动检测法的轮对踏面故障监测系统，通过傅里叶变换、小波包分析对釆集到的振动信号进行分析获得信号的特征,研究了基于短时能量判断的踏面故障特征提取算法。(On line monitoring system for wheel tread of urban rail vehicles, based on the vibration detection method of wheel tread fault monitoring system, through the Fu Liye transform, wavelet packet analysis of the collected vibration signals to obtain the characteristics of the signal, the study of the short-term energy judgment based on the feature extraction algorithm.)

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支持向量机的MATLAB源程序，效果真的很不错(SVM MATLAB source, the effect is really very good)

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利用TMS320VC5509A为核心的DSP处理硬件,通过软件实现自适应Notch滤波和瞬时频率序列方差检测(VIRD)运算,在较低信噪比使用条件下完成对单频测距信号的可靠检测和判定(Using tms320vc5509a DSP core processing hardware, adaptive notch filter and variance of instantaneous frequency sequence detection (Vird) operation is realized by software, in low signal to noise ratio under the conditions of use complete reliable detection of single frequency ranging signal and judging)

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本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

2011-01-25 19:06:47下载

积分：1
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利用维纳滤波实现噪声中的语音信号恢复，产生chirp信号，噪声为高斯白噪声，噪声叠加在chirp信号上，构成观测信号x(n),使用编程方法实现使用维纳滤波滤除高斯噪声。(Wiener filtering the voice signal recovery in the noise generated chirp signal, the noise is Gaussian white noise, noise superimposed on the chirp signal, constitute the observed signal x (n), using the programming method using the Wiener filter filter Gaussian noise.)

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【实例简介】

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模式识别应用范围广泛，在机器学习，图像处理，运动目标检测与跟踪方面具有较大的应用价值。是本好书，值得推荐。(pattern recognition applied extensively in machine learning, image processing, moving target detection and tracking with greater value. Is a book worth recommending.)

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这个函数分配一个数据缓冲区与多个颜色指定系统上的乐队。这种类型的缓冲区允许表示彩色图像(例如,RGB)。这个函数为每个指定分配缓冲区,一个二维表面颜色乐队。您可以使用MbufAlloc1d()和MbufAlloc2d()来创建单独的乐队一或二维数据缓冲区,分别。分配一个缓冲区后,我们建议您检查是否操作成功,使用MappGetError(),或通过验证,不是M_NULL返回的缓冲区的标识符。(This function allocates a data buffer with multiple color bands on the specified system. This type of buffer allows for the representation of color images (for example, RGB). This function allocates buffers that have a two-dimensional surface for each specified color band. You can use MbufAlloc1d() and MbufAlloc2d() to create single band one- or two-dimensional data buffers, respectively. After allocating a buffer, we recommend that you check if the operation was successful, using MappGetError(), or by verifying that the buffer identifier returned is not M_NULL.)

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积分：1

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