Search - haar-wavelet

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【JSP/Java】 CBIR DL : 0: Content based image retrieval in java using k-means clustering and haar wavelet transform
Update : 2024-05-18 Size : 5441536 Publisher : hsaka
【matlab】 signal_compression DL : 0: 用haar小波对信号进行3层分解，在对分解后的信号进行压缩，比较原信号和压缩后的信号-Haar wavelet signal decomposition layer 3 signal, the signal decomposition is compressed, and the compressed original signal after comparing the
Update : 2024-05-18 Size : 1024 Publisher : buewongmui
【ELanguage】 haar_decomposition DL : 0: These are the files for haar wavelet decomposition written in C .-These are the files for haar wavelet decomposition written in C .
Update : 2024-05-18 Size : 1024 Publisher : group4
【Other】 View.java DL : 0: Haar Wavelet Transforamtion
Update : 2024-05-18 Size : 1024 Publisher : yng1905+
【Embeded-SCM Develop】 Haarfilter DL : 0: haar 小波电网滤波模拟可作为电力电子课程设计DATAPLAY.M 为信号源DISPART.M 为分辨1函数DISPART1.M 为分辨2函数RECOVER1.M 为还原函数，输出滤波结果-haar wavelet filter simulation grid can be used as power electronics curriculum design DATAPLAY.M to distinguish between a signal source DISPART.M as a function DISPART1.M to distinguish two functions RECOVER1.M to restore the function, the output filter the results
Update : 2024-05-18 Size : 2048 Publisher : heydono
【Wavelet】 haarfenjie DL : 0: 形态学HAAR小波分解算法，用形态学算子替代了原有的小波分解算子，使其在边缘细节的处理更好。-Morphological HAAR wavelet decomposition algorithm, using morphological operators to replace the original wavelet decomposition operator to handle better edge detail in.
Update : 2024-05-18 Size : 1024 Publisher : 邓文豪
【Special Effects】 98764244haar DL : 0: 基于小波haar的图像处理程序，matlab-Based on the haar wavelet transform related procedures, matlab
Update : 2024-05-18 Size : 8209408 Publisher : 刘梓晨
【Special Effects】 wavelet DL : 0: 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
Update : 2024-05-18 Size : 1024 Publisher : lucy
【Wavelet】 Water-marking-using-Har-wavelet-transform DL : 0: the Matlab project contains the source code used for simple watermarking using wavelet transform. Performs watermarking of the input image by decomposing the image using haar wavlet. Noise generated with normal distribution is used as the key and is added to the input image to obtain the watermarked image.
Update : 2024-05-18 Size : 1024 Publisher : santosh
【2D Graphic】 haar-2d DL : 0: haar 2d wavelet transformation
Update : 2024-05-18 Size : 7995392 Publisher : ggson
【Software Engineering】 corrected-journal DL : 0: haar wavelet compression and encryption
Update : 2024-05-18 Size : 743424 Publisher : senthil
【Other】 JCBIR DL : 0: Content-Based Image Retri (CBIR) allows to automatically extracting target images according to objective visual contents of the image itself. Representation of visual eatures and similarity match are important issues in CBIR. In his paper a novel CBIR method is proposed by exploit the wavelets which represent the visual feature. We use Haar and D4 wavelet to decompose color images into multilevel scale and wavelet coefficients, with which we perform image feature extraction and similarity match by means of F-norm theory. Furthermore, we also provide a progressive image retri strategy to achieve flexible CBIR. We tested five categories of color images in the experiments. The retri performance of D4 and Haar wavelet is compared with wavelet histograms in erms of recall rate and retri speed. Experiment results reflect the importance of wavelets in CBIR and F-norm theory along with progressive retri strategy achieves efficient retri . -Content-Based Image Retri (CBIR) allows to automatically extracting target images according to objective visual contents of the image itself. Representation of visual eatures and similarity match are important issues in CBIR. In his paper a novel CBIR method is proposed by exploit the wavelets which represent the visual feature. We use Haar and D4 wavelet to decompose color images into multilevel scale and wavelet coefficients, with which we perform image feature extraction and similarity match by means of F-norm theory. Furthermore, we also provide a progressive image retri strategy to achieve flexible CBIR. We tested five categories of color images in the experiments. The retri performance of D4 and Haar wavelet is compared with wavelet histograms in erms of recall rate and retri speed. Experiment results reflect the importance of wavelets in CBIR and F-norm theory along with progressive retri strategy achieves efficient retri .
Update : 2024-05-18 Size : 2514944 Publisher : santhosh d
【Special Effects】 code DL : 0: 图形图像的小波变换，其中包括多分辨率分析，Gabor分辨率分析，Haar小波，高维小波等。-Graphic images of wavelet transform, including multiresolution analysis, Gabor resolution analysis, Haar wavelet, higher dimensional wavelet, etc.
Update : 2024-05-18 Size : 4096 Publisher : 李阳
【matlab】 5 DL : 0: 给出五种常用小波基的时域和频域波形图,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。-The time domain and frequency domain waveform diagram of five kinds of wavelet bases, wavelet base is Haar wavelet, Daubechies wavelet, Mexican (dbN) Hat (mexh) wavelet, Morlet wavelet, Meyer wavelet and 5.
Update : 2024-05-18 Size : 59392 Publisher : 叶斌
【Special Effects】 imdwt DL : 0: 稀疏重建与压缩感知源代码，对一幅图像lena进行M尺度的Haar小波变换-Sparse Reconstruction and compressive sensing source code, to be an image lena M scale Haar wavelet transform
Update : 2024-05-18 Size : 216064 Publisher : 叶圣超
【Wavelet】 haar DL : 0: 对2维图像进行小波变换，滤除图像中的噪声，提取轮廓信息。-Wavelet transform is carried out for 2 dimensional image, and the noise of the image is filtered, and the contour information is extracted..
Update : 2024-05-18 Size : 2048 Publisher : LZ
【Software Engineering】 demodulation-of-MFSK-signals DL : 0: 提出了一种多迸制频移键控(M娲K)信号调制分类及解调方法，选取截获接收机输出的MFSK信号的时频脊线作为分类特征，利用无监督聚类算法求取最佳聚类数M．利用时频脊线的Ham：小波变换估计码元宽度，并且利用对应最佳聚类数的聚类中心确定抽判门限，通过对时频脊线抽样判决，实现了 MFSK信号的解调．理论分析和对实际信号的处理结果证明了此算法的可行性．-new algorithm is proposed for elassillcation and demodulation of MFSK signals．The ridge of time— frequency representation of MFSK signals is analyzed．Modulation elassi_fieation is realized by using the unsupervised clustering algorithm to determine the optimal nulnllt2r of clusters．In order to demodulate MFSK signals，the Haar wavelet transform is used to estimate the code—width and the centers of optimal clusters are used to determine thresholds．Theoretical analysis and practical signal processing results justify the robusticity and the efficiency of the new classification and demodulation Mgorithm．
Update : 2024-05-18 Size : 219136 Publisher : 张洋
【Other】 haarTransform DL : 0: haar小波变换例子，能够帮助深入了解小波变换的基本概念-haar wavelet transform
Update : 2024-05-18 Size : 2048 Publisher : coco
【VHDL-FPGA-Verilog】 dwt_32 DL : 0: Haar wavelet for an image of 32*32.
Update : 2024-05-18 Size : 1024 Publisher : Rishi
【Technology Management】 surf DL : 0: SURF意指加速的具有鲁棒性的特征，由Bay在2006年首次提出，这项技术可以应用于计算机视觉的物体识别以及3D重构中。SURF算子由SIFT算子改进而来，一般来说，标准的SURF算子比SIFT算子快好几倍，并且在多幅图片下具有更好的鲁棒性。SURF最大的特征在于采用了harr特征以及积分图像integral image的概念，这大大加快了程序的运行时间。-SURF (Speeded Up Robust Feature) is a robust local feature detector, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images.
Update : 2024-05-18 Size : 2418688 Publisher : 草

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