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于 2020-12-08 发布文件大小:1025KB

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本文讲述了一种基于图像颜色直方图的图像相似度的度量的方法,。并用Matlab实现，有源代码(This article describes a method based on the image color histogram image similarity measure. And using Matlab, source code)

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图像相似

........\3.jpg,41130,2010-02-26
........\31.jpg,42820,2010-02-26
........\32.jpg,32925,2010-02-26
........\GetRgbHist.m,661,2010-09-05
........\imsimilar.m,714,2010-09-05
........\test.m,3048,2010-09-05
图像相似.doc,885248,2011-11-19

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imageprocessing6
1．选择一幅图像，对该图像进行DCT块操作（将图像分成8×8小块，对每个小块进行DCT变换）。 2.利用屏蔽矩阵对DCT系数进行区域选择，然后进行逆变换（IDCT），合成原图像，计算合成图像的PSNR。 3.选择一小波函数，对一幅图像进行分解，显示各变换系数，观察其规律，并进行小波逆变换，合成原图像。 (1. Select an image, the image DCT block operations (the image is divided into 8 × 8 small pieces of each small piece for DCT transform). 2. The use of shielding on the DCT coefficient matrix of regional choices, and then inverse transform (IDCT), synthesis of the original image, calculating the synthetic image PSNR. 3. To select a wavelet function, decomposition of an image to show the transform coefficients, to observe its laws, and inverse wavelet transform, the original synthetic image.)

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基于meanshift算法最全面的资料收集，是本人长期收集该算法的结晶，里面有均值漂移算法的word文档，PPT资料，基于meanshift的目标跟踪算法（MATLAB），还有相应的文章，下了绝不后悔，将心比心，互惠互利。(Meanshift algorithm based on the most comprehensive data collection, is a long time, I collected the crystallization of the algorithm, which has mean-shift algorithm word document, PPT data, meanshift target tracking algorithm based on (MATLAB), there is a corresponding article, in no way under the regret, Care, and mutual benefits.)

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车道偏离识别的程序，采用的是动态规划算法，对弯道也有比较高的识别率(lane departure algorithm, which has good performance even for curve lane.)

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说明：多尺度加权的rentinex算法实现图像增强，里面用到了高斯滤波对图像进行滤波，可以去除大部分的噪声，平滑图像效果较突出，3个高斯尺度对图像做滤波后加权在一起得到多尺度信息的图像。(Multiscale weighted rentinex algorithm is used to enhance the image. Gauss filter is used to filter the image, which can remove most of the noise. The smoothing effect of the image is prominent. Three Gaussian scales are filtered and weighted together to get the multi-scale information of the image.)

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