Description: Description: Recent studies on Mathematical modeling of visual cortical cells [Kulikowski/Marcelja/Bishop:1982] suggest a tuned band pass filter bank structure. These filters are found to have Gaussian transfer functions in the frequency domain. Thus, taking the Inverse Fourier Transform of this transfer function we get a filter characteristics closely resembling to the Gabor filters. The Gabor filter is basically a Gaussian (with variances sx and sy along x and y-axes respectively) modulated by a complex sinusoid (with centre frequencies U and V along x and y-axes respectively). Platform: |
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Author:gz |
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Description: Description: Recent studies on Mathematical modeling of visual cortical cells [Kulikowski/Marcelja/Bishop:1982] suggest a tuned band pass filter bank structure. These filters are found to have Gaussian transfer functions in the frequency domain. Thus, taking the Inverse Fourier Transform of this transfer function we get a filter characteristics closely resembling to the Gabor filters. The Gabor filter is basically a Gaussian (with variances sx and sy along x and y-axes respectively) modulated by a complex sinusoid (with centre frequencies U and V along x and y-axes respectively). Platform: |
Size: 2048 |
Author:gz |
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Description: 该文件含有自适应滤波的四篇国外经典文章,其中有连续自适应滤波的结构,无迟延子带自适应滤波器构造,FIR滤波器的时频实现等域.是自适应滤波器构造的经典文献-the adaptive filter paper containing the four foreign classic articles, which are continuous adaptive filter structure, without delay subband adaptive filter structure, FIR filters achieve such time-frequency domain. adaptive filter is constructed of classic literature Platform: |
Size: 2697216 |
Author:单昊 |
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Description: 计算Gabor滤波器函数.
Gabor1.m:4个方向的Gabo滤波器模板的图像显示.
Gabor2.m:4个方向的Gabor滤波器对lena进行滤波的顶层调用模块.
gabor.m:绘制一个Gabor滤波器的空域和频域函数图.
compute.m:计算Gabor滤波器函数（要被上面3个模块调用，这3个模块彼此独立）-Gabor filter function calculation. Gabor1.m: 4 directions Gabo filter template image display. Gabor2.m: 4 directions of the Gabor filter for filtering lena call top-level module. Gabor.m: Drawing of a Gabor filter browser s airspace and frequency domain function Fig. compute.m: Calculation of Gabor filter function (to be above three modules call, this three modules independent of each other) Platform: |
Size: 1024 |
Author:赵立桐 |
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Description: 数字图像处理实验报告，包括灰度图像处理，各类噪声的处理，频率域等滤波器（巴特沃斯、高斯、理想滤波器）以及边缘处理、图像锐化等，含有全部MATLAB代码及实验步骤与结果分析等。-Digital image processing experiments, including gray-scale image processing, handle all kinds of noise, such as frequency domain filter (Butterworth, Gaussian, ideal filter), as well as the edge processing, image sharpening and so on, contains all the MATLAB code and experimental steps and results analysis. Platform: |
Size: 2200576 |
Author:Diana |
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Description: matlab下实现降噪，功率谱计算。％程序中设定采样点数为256个，采样频率为10000hz，
％输入信号为随机噪声和两个正弦的合成信号
％设定的滤波器的截止频率为3500hz
％通过挈比雪肤滤波器，运行程序，比较滤波前后的频域波形
％滤波去除了高频信号-matlab achieve noise reduction, power spectrum calculation. Sampling procedure set for 256 points, the sampling frequency of 10000hz, input signal for the random noise and the two sinusoidal signals synthetic filter set a cut-off frequency 3500hz manner than through the filter雪肤, run procedures, compared before and after filtering in frequency domain waveforms filtering in addition to high-frequency signals Platform: |
Size: 1024 |
Author:范范 |
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Description: 这是一个很好的频域分块自适应滤波的程序，应用于回声消除上，并与NLMS自适应滤波做了运行速度的比较,FLMS比NLMS快几十倍。-This is a very good frequency-domain block adaptive filtering procedure applied to echo cancellation, and comparison with the NLMS adaptive filter for speed, FLMS several times faster than the NLMS. Platform: |
Size: 661504 |
Author:宋知用 |
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Description: Design frequency domain Ideal, Butterworth and Gaussian band pass filters to filter the input image. Use your own grayscale picture as the input image. The filters must be passing frequencies between radius of 30 and 120 frequency components of the Fourier spectrum (30<D0<120).
- input image
- Fourier spectrum of the image
- Frequency domain filter function image
- Band pass filtered image- Design frequency domain Ideal, Butterworth and Gaussian band pass filters to filter the input image. Use your own grayscale picture as the input image. The filters must be passing frequencies between radius of 30 and 120 frequency components of the Fourier spectrum (30<D0<120).
- input image
- Fourier spectrum of the image
- Frequency domain filter function image
- Band pass filtered image Platform: |
Size: 1024 |
Author:mustafa |
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Description: 基于Gabor变换的图像纹理识别。
提出了一种改进的Gabor变换的图像纹理增强算法，将空域的纹理图像变换到联合空间频率域并将联合空间
频率域的能量分布作为掌纹的特征，Gobar滤波器在频域内对子块其主方向上频率能量分布进行滤波，特征向量进行了匹配
识别，增强特征纹线信息并对核心区域进行多方向空间频率能量滤波合成，同时也对滤波算法进行了优化，有效地减少了运
算量。-Gabor transform based image texture recognition. An improved image of the Gabor transform texture enhancement algorithm, the airspace of the texture image transform frequency domain to the joint space and joint space frequency domain characteristics of the energy distribution as a palm, Gobar filter pair in the frequency domain block its the main direction of the energy distribution of the frequency filtering, feature vectors were matched to identify, enhance the features of ridge information as well as the core region of multi-dimensional spatial frequency energy filter synthesis, but also on the filtering algorithm has been optimized, effective in reducing the computational complexity. Platform: |
Size: 820224 |
Author:爱学习 |
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Description: 频域的卡尔曼滤波器，这个比较有意思，有兴趣的朋友可以看看，是一篇论文-THE EXTENDED KALMAN FILTER IN THE FREQUENCY DOMAIN FOR THE IDENTIFICATION OF MECHANICAL STRUCTURES EXCITED BY SINUSOIDAL MULTIPLE INPUTS Platform: |
Size: 175104 |
Author:ywauto |
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Description: 图像频域增强,频域低通滤波所产生的模糊,理想低通过滤波器所产生的模糊和振铃现象-Frequency-domain image enhancement, fuzzy frequency domain generated by the low-pass filtering, blurring and ringing the ideal low-pass filter is generated Platform: |
Size: 1024 |
Author:app |
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Description: 本文主要研究了频域滤波中平滑以及锐化技术，借助Butterworth滤波器以及Gauss滤波器探究了低通滤波器的性质；结合USM技术，Laplacian算子、以及Butterworth/Gauss滤波器研究了高通滤波器的特性.
doc文档最后附有所有我编写的的matlab代码-This paper studies the frequency domain filtering smoothing and sharpening techniques, using Gauss filter Butterworth filter and explores the nature of the low-pass filter combined USM technology, Laplacian operator, and Butterworth/Gauss filter to study the high-pass filter characteristics. doc document with all my final written matlab code Platform: |
Size: 1626112 |
Author:du han |
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Description: The reason for doing the filtering in the frequency domain is generally because it is computationally faster to perform two 2D Fourier transforms and a filter multiply than to perform a convolution in the image (spatial) domain. This is particularly so as the filter size increases.
In what follows it is assumed that the reader is familiar with the Discrete Fourier Transform, its properties, and the transforms of commonly used functions (delta, noise, rectangular pulse, step, etc). Platform: |
Size: 208896 |
Author:faisel |
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Search - frequency domain filter