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2下载：
图像复原逆滤波法matlab实现
和增强比较。,Image Restoration matlab inverse filtering method to achieve and enhance the comparison.
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二维傅里叶变换,对图像进行二维傅里叶变换处理-Two-Dimensional Fast Fourier Transform
The purpose of this project is to develop a 2-D FFT program "package" that will be used
in several other projects that follow. Your implementation must have the capabilitie
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比较反滤波和维纳滤波对一幅图像复原的效果。从两方面出发，一是对运动模糊和均值模糊复原的能力，二是抗噪能力，各种情况分别都进行了对比-Comparison of inverse filtering and Wiener filtering on an image restoration results. Proceed in two ways, first on the motion blur and the mean fuzzy recovery capability and noise imm
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应用多种滤波器进行处理：算术均值，几何
均值，谐波均值，逆谐波均值，中值滤波，
中点滤波，最大值、最小值滤波等-To deal with a variety of filter applications: arithmetic mean, geometric mean, harmonic mean, inverse harmonic mean, median filter, the mid-point filtering, maximum, minimum filtering
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逆滤波图像复原程序，可以根据情况在上面做修改-Inverse filtering image restoration procedure, you can make changes according to the situation in the above
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BACKPROJ uses the filtered or unfiltered backprojection algorithm to perform the inverse Radon transform. The filter is designed directly in the frequency domain and then multiplied by the FFT of the projections. The projections are zero-padded to a
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This MATLAB exercise designs and implements a pitch period detector based on detecting and tracking peaks in the autocorrelation of the LPC error signal during regions of voiced speech. The pitch detection procedure is called the SIFT (Simple Inverse
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IDW距离反比加权方法，在matlab R2009b调试通过，GPS和INS组合导航程序，大学数值分析算法，现代信号处理中谱估计在matlab中的使用，对信号进行频谱分析及滤波，包含优化类的几个简单示例程序。- IDW inverse distance weighting method, In matlab R2009b debugging through, GPS and INS navigation program, University of numerical analysis algo
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一些自适应信号处理的算法，与理论分析结果相比，采用的是脉冲对消法，信号处理中的旋转不变子空间法，IDW距离反比加权方法，滤波求和方式实现宽带波束形成，music高阶谱分析算法，现代信号处理中谱估计在matlab中的使用。- Some adaptive signal processing algorithms, Compared with the results of theoretical analysis, It uses a pulse of consumer law, Signal Pro
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在matlab R2009b调试通过，是学习PCA特征提取的很好的学习资料，滤波求和方式实现宽带波束形成，合成孔径雷达（SAR)目标成像仿真，基于负熵最大的独立分量分析，IDW距离反比加权方法，最小均方误差（MMSE）的算法，LCMV优化设计阵列处理信号。- In matlab R2009b debugging through, Is a good learning materials to learn PCA feature extraction, Filtering summation wa
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在matlab R2009b调试通过，是学习PCA特征提取的很好的学习资料，滤波求和方式实现宽带波束形成，合成孔径雷达（SAR)目标成像仿真，基于负熵最大的独立分量分析，IDW距离反比加权方法，最小均方误差（MMSE）的算法，LCMV优化设计阵列处理信号。- In matlab R2009b debugging through, Is a good learning materials to learn PCA feature extraction, Filtering summation wa
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The aims to give the students the fundamentals of digital image processing,
covering topics from the following list: image models and physical imaging systems;
visual perception; rendering systems; linear filtering; linear transforms; mathematical
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