Description: 平滑滤波 一般来说，图像的能量主要集中在其低频部分，噪声所在的频段主要在高频段，同时系统中所要提取的汽车边缘信息也主要集中在其高频部分，因此，如何去掉高频干扰又同时保持边缘信息，是我们研究的内容。为了去除噪声，有必要对图像进行平滑，可以采用低通滤波的方法去除高频干扰。图像平滑包括空域法和频域法两大类，在空域法中，图像平滑的常用方法是采用均值滤波或中值滤波，对于均值滤波，它是用一个有奇数点的滑动窗口在图像上滑动，将窗口中心点对应的图像像素点的灰度值用窗口内的各个点的灰度值的平均值代替，如果滑动窗口规定了在取均值过程中窗口各个像素点所占的权重，也就是各个像素点的系数，这时候就称为加权均值滤波；对于中值滤波，对应的像素点的灰度值用窗口内的中间值代替。实现均值或中值滤波时，为了简便编程工作，可以定义一个n*n的模板数组。另外，读者需要注意一点，在用窗口扫描图像过程中，对于图像的四个边缘的像素点，可以不处理；也可以用灰度值为\"0\"的像素点扩展图像的边缘。下面给出了采用加权均值滤波的图像平滑函数代码和效果图：-smoothing filter general, the image of energy is mainly focused on the low-frequency part of the noise lies mainly in the high-frequency band, which system to extract the vehicle Edge Information has been concentrated in some of its high frequency, therefore, how to remove high-frequency interference at the same time, maintain the edge information, we Institute enforcement of the content. In order to remove noise, it is necessary for smooth images can be used to the low-pass filter to remove high-frequency interference. Image Smoothing including airspace and frequency domain method two categories, in the airspace law, the common image smoothing method is used Mean Median filter or filter for filtering mean, it is an odd point in the sliding window on the sliding images of the corresponding Platform: |
Size: 43854 |
Author:123 |
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Description: 平滑滤波 一般来说，图像的能量主要集中在其低频部分，噪声所在的频段主要在高频段，同时系统中所要提取的汽车边缘信息也主要集中在其高频部分，因此，如何去掉高频干扰又同时保持边缘信息，是我们研究的内容。为了去除噪声，有必要对图像进行平滑，可以采用低通滤波的方法去除高频干扰。图像平滑包括空域法和频域法两大类，在空域法中，图像平滑的常用方法是采用均值滤波或中值滤波，对于均值滤波，它是用一个有奇数点的滑动窗口在图像上滑动，将窗口中心点对应的图像像素点的灰度值用窗口内的各个点的灰度值的平均值代替，如果滑动窗口规定了在取均值过程中窗口各个像素点所占的权重，也就是各个像素点的系数，这时候就称为加权均值滤波；对于中值滤波，对应的像素点的灰度值用窗口内的中间值代替。实现均值或中值滤波时，为了简便编程工作，可以定义一个n*n的模板数组。另外，读者需要注意一点，在用窗口扫描图像过程中，对于图像的四个边缘的像素点，可以不处理；也可以用灰度值为"0"的像素点扩展图像的边缘。下面给出了采用加权均值滤波的图像平滑函数代码和效果图：-smoothing filter general, the image of energy is mainly focused on the low-frequency part of the noise lies mainly in the high-frequency band, which system to extract the vehicle Edge Information has been concentrated in some of its high frequency, therefore, how to remove high-frequency interference at the same time, maintain the edge information, we Institute enforcement of the content. In order to remove noise, it is necessary for smooth images can be used to the low-pass filter to remove high-frequency interference. Image Smoothing including airspace and frequency domain method two categories, in the airspace law, the common image smoothing method is used Mean Median filter or filter for filtering mean, it is an odd point in the sliding window on the sliding images of the corresponding Platform: |
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Author: |
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Description: 该程序在matlab平台上实现了用最佳提取图像边缘的canny算子提取整副图像的边缘象素.
其中利用高斯函数滤除噪声和用高斯算子的一阶微分对图像滤波合并为一个算子,通过形态学算子将两幅图像的边缘进行连接.-The program in matlab platform to achieve the best extraction of the canny edge operator extract the whole image edge pixel deputy. Which use Gaussian function to filter out the noise and the use of Gaussian operator of the first-order differential of the image filtering into an operator, through morphological operators to the brink of two images connect. Platform: |
Size: 5120 |
Author:秀秀 |
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Description: (1)利用高斯滤波器函数，用Matlab语言，编写Canny边缘检测器的Matlab（或C语言）函数；
(2)利用上述函数，对一副图像（椒盐噪声或高斯噪声）进行边缘检测；
(3)利用Matlab自带的Canny边缘检测函数对同一副图像进行边缘检测；
(4)比较上述两个结果。
-(1) the use of Gaussian filter function, using Matlab language, the preparation of Canny edge detector Matlab (or C language) function (2) the use of the above-mentioned function, an image of the (salt and pepper noise or Gaussian noise) for edge detection (3) the use of Matlab built-in Canny edge detection function to the same Vice-image edge detection (4) compare the results of the two. Platform: |
Size: 2048 |
Author:amy |
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Description: 本实验要求编写一个中值滤波的程序，并对产生的椒盐噪声的图像进行中值滤波处理。中值滤波是基于统计学的一种非线性滤波方法。我们还需要知道一个按大小排列的数组中间位置上的数据称为是中值。通过修改在实验project03-04的程序实现3*3中值滤波。-Prepared in this experiment, a median filtering process, and salt and pepper noise generated by the image processing median filter. Median filter is based on a statistical non-linear filtering method. We also need to know the size of an order by the middle of the array data is referred to as value. By modifying the project03-04 in the experimental procedures for the realization of 3* 3 median filter. Platform: |
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Author:jhm |
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Description: 本文论述并设计实现了一个脱机自由手写体数字识别系统。文中首先对待识别数字的预处理进行了介绍，包括二值化、平滑滤波、规范化、细化等图像处理方法；其次，探讨了如何提取数字字符的结构特征和笔划特征，并详细地描述了知识库的构造方法；最后采用了以知识库为基础的模板匹配识别方法,并以MATLAB作为编程工具实现了具有友好的图形用户界面的自由手写体数字识别系统。实验结果表明，本方法具有较高的识别率，并具有较好的抗噪性能。-In this paper, designed and implemented an off-line handwritten numeral recognition system. The paper first pre-treatment identification numbers were introduced, including binarization, smoothing filter, normalization, thinning and other image processing methods secondly, to explore how to extract the number of characters in the structural characteristics and stroke features, and described in detail Knowledge of construction methods finally adopted in order to Knowledge-based template matching recognition method, and to MATLAB as a programming tool to achieve a friendly graphical user interface handwritten numeral recognition system. The experimental results show that this method has higher recognition rate, and has good anti-noise performance. Platform: |
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Author:zhangying |
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Description: 将K均值算法用于图像分割,输入的是彩色图像,转换为灰度图像进行分割,输出结果为灰度图像.利用灰度做为特征对每个像素进行聚类,由于光照等原因,有时应该属于一个物体的像素,其灰度值也会有很大的差别,可能导致对该像素的聚类发生错误.在分割结果中,该物体表面会出现一些不同于其它像素的噪声点,因此,算法的最后,对结果进行一次中值滤波,以消除噪声,达到平滑图像的作用-The K means algorithm for image segmentation, the input is a color image, convert to grayscale image segmentation, the output of grayscale images. The use of gray as the characteristics of each pixel clustering, due to light and other reasons, and sometimes should belong to an object pixel, its gray value will also be very different, may lead to clustering of the pixel error has occurred. in the segmentation results, the surface, there would be different from other pixel noise points, so , the algorithm Finally, the results of a median filter to eliminate noise, to the role of smoothing the image Platform: |
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Author:caoliang |
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Description: NAME:
bpass
PURPOSE:
Implements a real-space bandpass filter which suppress
pixel noise and long-wavelength image variations while
retaining information of a characteristic size.
CATEGORY:
Image Processing
CALLING SEQUENCE:
res = bpass( image, lnoise, lobject )
INPUTS:
image: The two-dimensional array to be filtered.
lnoise: Characteristic lengthscale of noise in pixels.
Additive noise averaged over this length should
vanish. MAy assume any positive floating value.
lobject: A length in pixels somewhat larger than a typical
object. Must be an odd valued integer.
OUTPUTS:
res: filtered image.
PROCEDURE:
simple wavelet convolution yields spatial bandpass filtering.
NOTES:-NAME:
bpass
PURPOSE:
Implements a real-space bandpass filter which suppress
pixel noise and long-wavelength image variations while
retaining information of a characteristic size.
CATEGORY:
Image Processing
CALLING SEQUENCE:
res = bpass( image, lnoise, lobject )
INPUTS:
image: The two-dimensional array to be filtered.
lnoise: Characteristic lengthscale of noise in pixels.
Additive noise averaged over this length should
vanish. MAy assume any positive floating value.
lobject: A length in pixels somewhat larger than a typical
object. Must be an odd valued integer.
OUTPUTS:
res: filtered image.
PROCEDURE:
simple wavelet convolution yields spatial bandpass filtering.
NOTES: Platform: |
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Author:santhu |
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Description: 图像的平滑与增强是数字图像处理过程中的重要步聚,图像平滑可以消减噪声,但会丢失细节,增强可以突出
边缘但同时会放大噪声。为了解决图像平滑与增强之间的矛盾关系,提出一种图像的自适应平滑与增强方法,在进行滤波
时,动态确定所处理像素点的滤波权值,在平滑了图像区域内部的同时,又对图像中的区域边缘进行锐化增强,有效解决了
图像平滑与增强的矛盾。-The image smoothing and enhancement of digital image processing of the important steps, in image smoothing can be reduced and the noise, but will lose detail, enhanced to highlight the edges, but will also enlarge the noise. Image smoothing and enhancement in order to solve the contradictory relationship between the proposed adaptive smoothing and an image enhancement method, during filtering, the dynamic processing to determine the pixel filter weights, in smooth image regions within the same time, right in the image edge sharpening to enhance the region to effectively solve the contradiction between image smoothing and enhancement. Platform: |
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Author:malei |
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Description: 为了在抑制噪声时尽可能保留图像边缘信息，提出一种自适应各向异性高斯滤波器设计方法. 该方法由独立
强度传播（IDS）模型决定滤波器的长轴尺度，由像素的邻域平滑度决定长短轴的比例，然后根据该处的灰度梯度方
向自适应决定各向异性滤波器的长轴方向. 仿真实验表明，提出的自适应各向异性滤波器具有很强的噪声抑制和
边缘保持能力.
-In order to suppress noise, as far as possible to keep the image edge information, an adaptive anisotropic Gaussian filter design methods. The method by the independent strength spread (IDS) model determines the long axis of the filter scale, the pixel neighborhood smoothness determine the ratio of minor axis, and then there' s gray gradient direction of adaptive decision the long axis of anisotropic filter. Simulation results show that the proposed adaptive anisotropic filter has a strong noise suppression and preserve edges. Platform: |
Size: 207872 |
Author:wangcong |
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Description: canny edge detector. The program in matlab platform to achieve the best extraction of the canny edge operator extract the whole image edge pixel deputy. Which use Gaussian function to filter out the noise and the use of Gaussian operator of the first-order differential of the image filtering into an operator, through morphological operators to the brink of two images connect Platform: |
Size: 2048 |
Author:mokocom |
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Description: the noise deteriorates the
interpolation performance in digital images, it is effective to
employ denoising prior to the interpolation. In this paper, we
propose a novel interpolation framework in which denoising
and image sharpening methods are embedded. In the
proposed framework, the image is first decomposed using the
bilateral filter into the detail and base layers which represent
the small and large scale features, respectively. The detail
layer is adaptively smoothed to suppress the noise before
interpolation and an edge-preserving interpolation method is
applied to both layers. Finally, the high resolution image is
obtained by combining the base and detail layers.
Experimental results show that the proposed algorithm
outperforms the conventional methods Platform: |
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Author:prabhakaran |
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Description: 1. 用 butterworth和理想低通滤波器对受椒盐噪声和高斯噪声污染的图像进行平滑处理, 计算平滑前后的PSNR(峰值信噪比).
2. 用 3x3邻域平均平滑和3x3中值滤波对受椒盐噪声和高斯噪声污染的图像进行平滑处理, 计算平滑前后的PSNR(峰值信噪比).
3. 用 roberts算子和Laplace算子对一图像进行锐化处理, 得到其边缘二值图像.-Salt and pepper noise and Gaussian noise images with butterworth and the ideal low-pass filter for smoothing, calculating smooth before and after the PSNR (peak signal to noise ratio).
(2) 3x3 neighborhood average in smoothing and 3x3 median filter images by the salt and pepper noise and Gaussian noise smoothing, computing smooth around the PSNR (peak signal to noise ratio).
Roberts operator and Laplace operator on an image sharpening, get the edge binary image. Platform: |
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Author:Xucheng |
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Description: The median filter is normally used to reduce noise in an image, somewhat like the mean filter. However, it often does a better job than the mean filter of preserving useful detail in the image.-The median filter is normally used to reduce noise in an image, somewhat like the mean filter. However, it often does a better job than the mean filter of preserving useful detail in the image.
Platform: |
Size: 1024 |
Author:tarik zahouane |
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Description: 1 打开一个BMP文件，将其局部区域的灰度值进行改变，另存为一个新的BMP文件，要求显示出原BMP图像和新BMP图像。
2．编程实现图像傅立叶高通、低通滤波。
3.打开一幅图像，添加椒盐、高斯噪声，然后使用邻域平均法、中值滤波法、K邻近平均法进行平滑
4.打开一幅图像，利用Roberts梯度法、Sobel算子和拉普拉斯算子进行锐化，并比较结果。
5.编写一个程序，对输入的图像进行哈夫曼编码，显示原图像的熵、编码后的平均码字长度、并能够根据编码重建出图像
6.在图像中生成一个矩形，然后用模板匹配法找出矩形位置。使用SSDA或改进的SSDA法。-1) open a BMP file, change the gray values of its local area, and save it as a BMP file, the request shows the original BMP images and BMP images.
2. Programming image Fourier high-pass, low-pass filtering.
3 Open an image, add salt and pepper, Gaussian noise, and then use the neighborhood average, median filter, K adjacent average method for smoothing
4 Open an image using the Roberts gradient method, Sobel operators and Laplacian sharpening for, and compare the results.
5 to write a program, Huffman coding of the input image, the display of the original image entropy, and the average code word length of the encoded, and be able to reconstruct the image according to the coding
6. Generate a rectangle in the image, and then use the template matching method to identify the position of the rectangle. Using SSDA or improved SSDA method. Platform: |
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Author:fei |
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Description: 在信号处理中，它通常是可取的是能够执行某种降噪图像或信号。中值滤波是一种非线性数字滤波技术，通常用于去除噪声。这种噪声是一个典型的前处理步骤，提高后处理的结果（例如，边缘检测在图像）。中值滤波是非常广泛的应用在数字图像处理中，在一定的条件下，它保留了边缘，去除噪声-In signal processing, it is often desirable to be able to perform some kind of noise reduction on an image or signal. The median filter is a nonlinear digital filtering technique, often used to remove noise. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image). Median filtering is very widely used in digital image processing because, under certain conditions, it preserves edges while removing noise Platform: |
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Author:Simon |
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Description: 中值滤波，去噪
实验原理：中值滤波器是将领域内像素灰度的中值代替该像素的值,对处理脉冲噪声(椒盐噪声)非常有效。为了对一幅图像上的某个点进行中值滤波处理，必须先将掩模内欲求的像素及其领域的像素值排序，确定出中值，主要功能是使拥有不同灰度的点看起来更接近于它的邻近值。-Median filtering and denoising
Test principle: median filter is to field pixel gray value instead of the pixel value, to deal with impulse noise (salt and pepper noise) is very effective. To a certain point in an image processing median filtering, must first to mask the desires of the pixel and the pixel values in the field of sorting, determine the median, the main function is to make with a different point of gray looks closer to its adjacent values. Platform: |
Size: 3072 |
Author:1123 |
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Description: 1)Simulate a case of a linear motion across 20 pixels at an angle of 30 degree
2)Add simulate noise to the blurred image
3)Apply the wiener filter to the blurred image
4)Computing the SNR (in dB) between the restored image and the original image Platform: |
Size: 295936 |
Author:ela |
Hits:
Search - noise filter in an image