Description: 哈尔小波变换源代码，自己写的，调试成功，可以参考，并与其他方式比较！-Haar wavelet transform source code, write your own, commissioning successful, can refer to and compare with other ways! Platform: |
Size: 157696 |
Author:chengxin |
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Description: Visual C++ 小波变换的各个函数，haar sym db coif，VC++小波工程变换所有章节代码-Visual C++ wavelet transform of each function, haar sym db coif Platform: |
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Author:刘岩 |
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Description: 复杂杂波背景下，海面红外图像中舰船目标检测的关键是如何降低虚警、检测出真正的
目标。为了实现这个目标，首先利用Haar小波函数进行小波变换，对图像进行预处理；然后进行恒
虚警检测（CFAR）；第三步采用行程法对检测的目标进行标记；最后采用管道滤波法剔出虚假目标，
检测出真正的目标。经仿真实验证明，此方法能有效地降低虚警，在复杂杂波背景中检测出目标。
-The key of ship detection in sea infrared image with complex clutter background is how to
reduce false alarms and detect true targets.In order to achieve this aim,a novel algorithm is proposed.
First,Haar wavelet transform technology is used as preprocessing,then constant false alarm rate(CFAR)
detetion,then run-length label to mark objects detected by the above step,finally pipeline filter to reduce
false alarms and detect true targets.Experiment results indicate that this method can effectively reduce false alarms and detect true targets in complicated sea background.
Platform: |
Size: 1636352 |
Author:majun |
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Description: 通过设计Visual C程序源码对简单易懂的一维信号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波与Haar小波变换，从而的到小波分解系数；再通过改变分解的到的各层高频系数数进行信号的小波重构达到消噪噪的目的。在这一程序源码实现的过程中能直观地理解信号小波分解重构的过程与在信号消噪中的重要作用，和在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。 可直接
-Design Visual C program source code on a simple one-dimensional signal with a Gaussian white noise Daubechies wavelet, Morlet wavelet and Haar wavelet transform, and thus to the wavelet coefficients and then change the decomposition to each storey wavelet reconstruction frequency coefficient of the number of signal to noise canceling noise. In the process of realization of this program source code can be intuitively understood the signal wavelet decomposition and reconstruction process and an important role in signal denoising, and the selection coefficient in the high frequency coefficients of the layers of the weight of processing noise cancellation signal impact. Can be directly Platform: |
Size: 160768 |
Author:xlli |
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Description: 运用OpenCv开发的一个一种基于adaboost算法与haar小波变换换的人脸算法，具体情况可参考Paul Viola ，Robust Real
-A use OpenCv development based adaboost algorithm haar wavelet transform to change the face algorithm, the specific circumstances of the reference, Paul Viola, Robust the Real Platform: |
Size: 1024 |
Author:卓越 |
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Description: To demonstrate the effectiveness of the proposed method, we
evaluated it by comparing it and the smoothing method based
on classical Haar wavelet transform (HWT) [3]. Platform: |
Size: 15194112 |
Author:rasul |
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Description: Haar小波变换，还有其他的相关变换TransformSparsify.m-Haar wavelet transform, as well as other related transform TransformSparsify.m Platform: |
Size: 1024 |
Author:燕玲 |
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Description: 基于Haar小波的图像变换方法的研究分析情况-Research and analysis based on the image of the Haar wavelet transform method Platform: |
Size: 121856 |
Author:Le |
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Description: MATLAB函数为pm哈尔1-D DWT算法
离散哈尔的基本原理小波变换-MATLAB function for pm Haar 1-D DWT algorithm,Fundamentals of the discrete Haar wavelet transform Platform: |
Size: 1024 |
Author:张成 |
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Description: MATLAB函数为pm Haar 1-D IDWT算法
离散Haar小波逆变换的基本原理-MATLAB function for pm Haar 1-D IDWT algorithm,
Fundamentals of the discrete Haar wavelet transform Platform: |
Size: 1024 |
Author:张成 |
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Description: Content based image retrieval in java using k-means clustering and haar wavelet transform Platform: |
Size: 5441536 |
Author:hsaka |
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Description: 与标准的傅里叶变换相比，小波分析中使用到的小波函数具有不唯一性，即小波函数 具有多样性。小波分析在工程应用中，一个十分重要的问题就是最优小波基的选择问题，因为用不同的小波基分析同一个问题会产生不同的结果。目前我们主要是通过用小波分析方法处理信号的结果与理论结果的误差来判定小波基的好坏，由此决定小波基。常用小波基有Haar小波、Daubechies(dbN)小波、Mexican Hat(mexh)小波、Morlet小波、Meyer小波等5种。-Compared with the standard Fourier transform, wavelet analysis using the wavelet function has not unique, ie wavelet function with diversity. Wavelet analysis in engineering applications, a very important issue is the optimal choice of wavelet problem because different wavelets analysis of the same problem will produce different results. At present we are mainly through the error processing results with the theoretical results signal using wavelet analysis method to determine the quality of wavelets, which determines the wavelets. Haar wavelets have used wavelet, Daubechies (dbN) wavelet, Mexican Hat (mexh) wavelet, Morlet wavelet, Meyer wavelet five species. Platform: |
Size: 59392 |
Author:邢龙 |
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Description: 傅里叶变换是用一系列不同频率的正余弦函数去分解原函数，变换后得到是原函数在正余弦不同频率下的系数。
小波变换使用一系列的不同尺度的小波去分解原函数，变换后得到的是原函数在不同尺度小波下的系数。
不同的小波通过平移与尺度变换分解，平移是为了得到原函数的时间特性，尺度变换是为了得到原函数的频率特性。
小波变换步骤：
1.把小波w(t)和原函数f(t)的开始部分进行比较，计算系数C。系数C表示该部分函数与小波的相似程度。
2.把小波向右移k单位，得到小波w(t-k)，重复1。重复该部知道函数f结束.
3.扩展小波w(t)，得到小波w(t/2)，重复步骤1,2.
4.不断扩展小波，重复1,2,3.
我这里使用的haar小波，缩放函数是[1 1]，小波函数是[1 -1]。-Fourier transform is a series of sine and cosine functions of different frequencies to the decomposition of the original function, after transform the original function in different frequency sine and cosine coefficients. Wavelet transform using a range of different scales of the wavelet decomposition to the original function, after transform the original function coefficients at different scales wavelets. Different wavelet decomposition by translation and scaling, translation is to get the time characteristics of the original function, in order to obtain the frequency scaling characteristics of the original function. Wavelet transform steps: 1. wavelet w (t) and the original function f (t) of the beginning of the comparison, calculate the coefficient C. The coefficient C indicates the degree of similarity of the function and wavelets. 2. Wavelet k units to the right, get the wavelet w (tk), repeat 1. Repeat this end portion know the function f. 3. Extended wavelet w (t), to obtain the Platform: |
Size: 1024 |
Author:lucy |
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Description: This paper proposes new watermarking technique based on Tetrolet domain. The Tetrolet transform is a new adaptive Haar-type wavelet transform based on tetrominoes. It avoids Gibbs oscillation because it applies the Haar function at the edge of the image. Our proposed watermarking algorithm embeds the watermark into the Tetrolet coefficients which are selected by considering different shapes of tetrominoes and uated the effectiveness of the watermarking approach by considering the quality metrics like RMSE, PSNR and Robustness parameters. The experimental results reveal that the proposed watermarking scheme is robust against common image processing attacks.-This paper proposes new watermarking technique based on Tetrolet domain. The Tetrolet transform is a new adaptive Haar-type wavelet transform based on tetrominoes. It avoids Gibbs oscillation because it applies the Haar function at the edge of the image. Our proposed watermarking algorithm embeds the watermark into the Tetrolet coefficients which are selected by considering different shapes of tetrominoes and uated the effectiveness of the watermarking approach by considering the quality metrics like RMSE, PSNR and Robustness parameters. The experimental results reveal that the proposed watermarking scheme is robust against common image processing attacks. Platform: |
Size: 1816576 |
Author:shaik |
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