Description: 用Matlab中的Haar和Db9小波对图像进行分解和重构,并在不同阈值下用PNG格式存储重构的图像.-Matlab Haar and the right image Db9 wavelet decomposition and reconstruction, and under different thresholds with PNG format image storage remodeling. Platform: |
Size: 33792 |
Author:昂清 |
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Description: 用GA训练BP网络的权值、阈值 。好的东西大家要共享啊。-GA training BP network with the weights, thresholds. U.S. to share the good things in ah. Platform: |
Size: 1024 |
Author:张玉 |
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Description: ostu图像分割阈值算法,对Ostu图像分割最优阈值进行优化处理，极大缩短了搜索图像阈值计算时间，与传统的枚举法Otsu方法相比,在计算时间上具有显著的优点。-ostu threshold image segmentation algorithm for image segmentation Ostu optimal thresholds to optimize the processing, greatly reduces the search image thresholding computation time, with the traditional enumeration method Otsu methods, in the calculation of time has significant advantages. Platform: |
Size: 167936 |
Author:李劲 |
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Description: 根据小波变换和噪声信号地能量分布特性，提出了一种先用小波变换对含噪图像进行多尺度分解，求出各尺度小波变换高频系数地噪声方差和阈值，利用各尺度地阈值对高频系数进行处理，然后利用小波变换系数重构图像，实现图像降噪地方法。-According to wavelet transform and noise signal and energy distribution characteristics, a first wavelet transform of the noisy image multiscale decomposition, obtained the high-frequency-scale wavelet transform coefficients and noise variance and thresholds, using the scale to the threshold value of the deal with high-frequency coefficients, and then the use of wavelet transform coefficients reconstructed image, to realize image denoising methods. Platform: |
Size: 519168 |
Author:wangrui |
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Description: 这段程序是用遗传算法优化神经网络权值和阈值的gaot工具箱-This procedure is to use genetic algorithms to optimize neural network weights and thresholds of gaot Toolbox Platform: |
Size: 1024 |
Author:wangwensheng |
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Description: 类间方差阈值分割是在最小二乘法原理基础上推导出来的,其基本思路是将直方图在某一阈值处理分割成两组,当被分成的两组的方差为最大时,决定阈值。-Otsu threshold segmentation is based on the principle of least square method derived, and its basic idea is to be a threshold in the histogram is separated into two groups of treatment, when the two groups were divided into the variance was the largest, the decision thresholds. Platform: |
Size: 1024 |
Author:孙建青 |
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Description: 利用遗传算法来训练BP神经网络的权值和阈值-The use of genetic algorithm to train the BP neural network weights and thresholds Platform: |
Size: 1024 |
Author:shui |
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Description: 1.对染噪doppler信号进行小波包3层分解：分解层次j=1,2时，都是信号的概貌；当j=3时，反映概貌的已几乎不含噪声分量，而其它噪声分量的幅值已很小。
2.对加噪Blocks信号进行不同阈值及不同阈值的使用方式降噪。
-1. On noise pollution doppler signal decomposition of wavelet packet Layer 3: decomposition level j = 1,2, are the signal profiles when j = 3 to reflect the general picture has been almost non-noise component, while other noise components amplitude has been very small. 2. Blocks of noise signals of different thresholds and different thresholds for the use of noise reduction methods. Platform: |
Size: 3072 |
Author: |
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Description: JPEG2000 Haar and inverse Haar wavelet transform on images.And a threshold can be added during the compression, and after decompression the result can be seen with different thresholds. Platform: |
Size: 3072 |
Author:lynn |
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Description: 实现对一幅灰度和彩色图像作的离散余弦变换,选择适当的DCT系数阈值对其进行DCT反变换.-The realization of a piece of gray and color images for the discrete cosine transform, select the appropriate thresholds for DCT coefficients of its inverse transform DCT. Platform: |
Size: 2048 |
Author:龙活 |
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Description: 两种阈值基于小波变换的阈值方法的比较和介绍，并给出了详细的说明-Two thresholds based on wavelet transform thresholding methods and the introduction and give a detailed description of Platform: |
Size: 194560 |
Author:黎明 |
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Description: OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.- OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images. Platform: |
Size: 2048 |
Author:ltrko9kd |
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Description: 程序代码说明
P0401：用Prewitt算子检测图像的边缘
P0402：用不同σ值的LoG算子检测图像的边缘
P0403：用Canny算子检测图像的边缘
P0404：图像的阈值分割
P0405：用水线阈值法分割图像
P0406：对矩阵进行四叉树分解
P0407：将图像分为文字和非文字的两个类别
P0408：形态学梯度检测二值图像的边缘
P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象-Procedure Code Description P0401: detection using Prewitt operator Edge P0402: σ values with different operator LoG edge detection image P0403: detection using Canny operator Edge P0404: Image Thresholding P0405: thresholds for water line image segmentation method P0406: for the matrix decomposition quadtree P0407: text and images are divided into two categories of non-text P0408: detection of morphological gradient of the edge binary image P0409: morphological examples- from the PCB to remove all images current lines, retaining only the target chip Platform: |
Size: 2048 |
Author:周鹏 |
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Description: The application works with non-compressed grayscale AVI files. Run mainGUI.p. Load AVI file first using "Load". To process the next frame use "Step". To run the application until stop, use "Run" and "Stop". You can draw the tracking object using mouse at any step. You can use the function on_threshold separately:
thresholded image = on_threshold(double( grayscale image ),1,number of thresholds)
thresholds value = on_threshold(double( grayscale image ),0, number of thresholds)
All the code provided is written in Matlab language (M-files and/or M-functions), with no dll or other protected parts of code (P-files or executables). The code was developed with Matlab 14 SP1. Matlab Image Processing Toolbox is required. Platform: |
Size: 102400 |
Author:Swati |
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Description: 利用遗传算法优化BP神经网络权值和阈值，然后进行训练，利用训练好的模型进行预估。附实例-The use of genetic algorithm to optimize BP neural network weights and thresholds, and then training, training a good use of forecast models. Attached examples Platform: |
Size: 20480 |
Author:汲平 |
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Description: 对比BP，OMP，StOMP对自然图像的重构效果,输入图像是一幅256*256的lena图像，我们使用压缩采样后，再用上述三种方法对其进行重构，比较其结果，其中StOMP方法是用不同的阈值-Contrast to BP, OMP, StOMP effect on the reconstruction of natural images, input image is a 256* 256 lena image, we use the compressed sampled, and then reconstruct them the above-mentioned three methods to compare their results, which StOMP method is to use different thresholds Platform: |
Size: 72704 |
Author:danliu |
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Description: 一个基于人工势场的机器人路径规划的仿真程序源码，可以自行修改阈值。-An artificial potential field based robot path planning simulation program source code, you can modify thresholds. Platform: |
Size: 21504 |
Author:采儿 |
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Description: ROC curves illustrate performance on a binary classification problem where classification is based on simply thresholding a set of scores at varying levels. Lenient thresholds give high sensitivity but low specificity, strict thresholds give high specificity but low sensitivity the ROC curve plots this trade-off over a range of thresholds (usually with sens vs 1-spec, but I prefer sens vs spec this code gives you the option).
It is theoretically possible to operate anywhere on the convex hull of an ROC curve, so this is plotted too. The area under the curve (AUC) for a ROC plot is a measure of overall accuracy, and the area under the ROCCH is a kind of upper bound on what might be achievable with a weighted combination of differently thresholded results from the given classifier
-ROC curves illustrate performance on a binary classification problem where classification is based on simply thresholding a set of scores at varying levels. Lenient thresholds give high sensitivity but low specificity, strict thresholds give high specificity but low sensitivity the ROC curve plots this trade-off over a range of thresholds (usually with sens vs 1-spec, but I prefer sens vs spec this code gives you the option).
It is theoretically possible to operate anywhere on the convex hull of an ROC curve, so this is plotted too. The area under the curve (AUC) for a ROC plot is a measure of overall accuracy, and the area under the ROCCH is a kind of upper bound on what might be achievable with a weighted combination of differently thresholded results from the given classifier
Platform: |
Size: 4096 |
Author:saadat |
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Description: 在基于前景检测的基于移动物体检测和车辆跟踪算法的实现中，针对广泛的应用来实现读取AVI文件，并将其分解为R，G和B组件。 执行各种操作并检测移动物体。 各个阶段的阈值决定了识别某些尺寸的移动物体的可能性。 移动物体也在其中跟踪。 MATLAB用于实现算法。 该算法用包含120帧的输入avi格式视频文件进行测试。 研究并实现了这些算法的各种应用。(In this foreground detection based moving object detection and vehicle tracking algorithm is implemented targeting a wide class of applications. An AVI file is read and it is decomposed into R, G and B components. Various operations are carried out and the moving objects are detected. Thresholds at various phases are decide the possibility of identifying the moving object of certain sizes. Moving objects also tracked in it. MATLAB is used for implementation of the algorithm. The algorithm is tested with input avi format video files consisting of 120 frames. Various applications of these algorithms are studied and implemented. Main focus is given on (unmanned aerial vehicle) UAV based and automatic traffic estimation applications) Platform: |
Size: 346112 |
Author:夙愿
|
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Description: PSO优化BP神经网络 MATLAB版本2016a PSO优化BP神经网络的权值和阈值 有详尽的注释 并结合2016a的新版本函数特性，优化了算法(PSO optimization BP neural network MATLAB version 2016a PSO optimization BP neural network weights and thresholds Detailed comments and combined with the 2016a new version of the functional characteristics of the optimization algorithm) Platform: |
Size: 48128 |
Author:哈利波特yhs |
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Search - thresholds matlab