Description: 由matlab编写，带GUI界面。对bmp文件进行Vector Quantization。运行其中的VQ_GUI.m文件。
程序肯定是调试无误的。虽然比较耗时，但是最后能达到较好的图像效果和SNR。毕竟相比于VC，matlab运行较慢。
注意在点open打开了一个bmp文件过后，一定要先点VQ code，进行其他操作才能有效。-prepared by Matlab, with GUI interface. Bmp files to Vector Quantization. VQ_GUI.m running the paper. Debugging procedure is certainly unmistakable. Although it is quite time-consuming, but in the end will get better images and SNR. After all, compared to the VC, Matlab run slower. Attention to the point of open open after a bmp file, you must first point VQ code, other operations to be effective. Platform: |
Size: 68323 |
Author:王嘉宁 |
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Description: 在MATLAB中编写实现图像的不同级别小波分解算法；2选择合适的小波基；3对经典的几幅黑白和彩色图像进行DWT变换；4实现零树、基于塔式网格矢量量化、基于LBG算法、基于标量量化等小波变换编码；5得到分析比较结果。达到的目的：1综合训练学生编程的能力；2对高数、计算方法、程序设计、数据结构、算法、数字图像处理等课程的复习和运用；3可培养学生的算法设计和分析能力。-in MATLAB prepared to achieve different levels of image wavelet decomposition algorithm; Choice of two small Porgy; Three pairs of classic pieces of black-and-white and color images DWT; Four zero tree, grid-based Tower vector quantization, LBG-based algorithm, based on the scalar quantization Wavelet Transform Coding ; 5 analyzed the results of the comparison. The purpose : a comprehensive training program students; Two pairs of the high number and the method of computation, programming, data structures, algorithms, digital image processing and review of the curriculum used; Three students can develop the algorithm design and analysis. Platform: |
Size: 34727 |
Author:aa |
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Description: 由matlab编写，带GUI界面。对bmp文件进行Vector Quantization。运行其中的VQ_GUI.m文件。
程序肯定是调试无误的。虽然比较耗时，但是最后能达到较好的图像效果和SNR。毕竟相比于VC，matlab运行较慢。
注意在点open打开了一个bmp文件过后，一定要先点VQ code，进行其他操作才能有效。-prepared by Matlab, with GUI interface. Bmp files to Vector Quantization. VQ_GUI.m running the paper. Debugging procedure is certainly unmistakable. Although it is quite time-consuming, but in the end will get better images and SNR. After all, compared to the VC, Matlab run slower. Attention to the point of open open after a bmp file, you must first point VQ code, other operations to be effective. Platform: |
Size: 67584 |
Author:王嘉宁 |
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Description: 在MATLAB中编写实现图像的不同级别小波分解算法；2选择合适的小波基；3对经典的几幅黑白和彩色图像进行DWT变换；4实现零树、基于塔式网格矢量量化、基于LBG算法、基于标量量化等小波变换编码；5得到分析比较结果。达到的目的：1综合训练学生编程的能力；2对高数、计算方法、程序设计、数据结构、算法、数字图像处理等课程的复习和运用；3可培养学生的算法设计和分析能力。-in MATLAB prepared to achieve different levels of image wavelet decomposition algorithm; Choice of two small Porgy; Three pairs of classic pieces of black-and-white and color images DWT; Four zero tree, grid-based Tower vector quantization, LBG-based algorithm, based on the scalar quantization Wavelet Transform Coding ; 5 analyzed the results of the comparison. The purpose : a comprehensive training program students; Two pairs of the high number and the method of computation, programming, data structures, algorithms, digital image processing and review of the curriculum used; Three students can develop the algorithm design and analysis. Platform: |
Size: 34816 |
Author:aa |
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Description: 提供了关于图像抽样、量化、均匀化、规定化及获得图像位面图的程序-provided on the image sampling, quantization, homogenization, and provides access to images of surface spaces of the processes Platform: |
Size: 2048 |
Author:王严 |
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Description: 基于标量量化的图像多描述编码（MDSQ）是提高信息传输质量的一种有效方法,本程序利用Matlab 工具在处理矩阵上的灵活性,实现了MDSQ 算法, 并通过解码后的图像证明该方法良好的多描述性能。-Scalar quantization-based image multiple description coding (MDSQ) is to improve the quality of information transmission of an effective method, the procedures for the use of Matlab tool flexibility matrix treatment, realized MDSQ algorithm, and through decoded images show that the method good performance of multiple description. Platform: |
Size: 297984 |
Author:shanyingying |
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Description: 已知两个不同图像块亮度数据如下：
（1）分析DCT原理，采用DCT方法，编程并计算相应的DCT系数，分析系数分布特点。
（2）依据视觉特性分析量化表步长的分布特点，完成DCT系数量化。
（3）采用Z形扫描，实现输出数据的统计编码，形成Video stream。
（4）采用IDCT重建图像亮度数据，计算SAD大小，分析产生误差的原因及采用DCT进行数据压缩的原理。（ ）
（5）分别利用左上角1、3、6个系数重建图像，计算相应的SAD，并由此分析直流和低频系数的重要性。
-Known brightness of two different image data block is as follows: (1) Principles of analysis of DCT, the DCT method, program and calculate the corresponding DCT coefficient, analysis of distribution coefficients. (2) quantitative analysis based on visual characteristics of the distribution of long-form features step-by-step to complete the DCT coefficient quantization. (3) the use of Z-scan output data to achieve statistical encoding, the formation of Video stream. (4) the use of the reconstructed image brightness IDCT data to calculate the SAD size, analysis of the causes of errors and the use of DCT for the principle of data compression. () (5), respectively, a factor of 1,3,6 using the upper left corner of the reconstruction of images, calculating the corresponding SAD, and the resulting analysis of DC and the importance of low-frequency coefficients. Platform: |
Size: 1024 |
Author:张元 |
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Description: 本程序是用matlab写的，实现对图像进行二维预测与Lloyd-Max量化压缩。是有损压缩。附有程序所用的图片。-The program is written in matlab to achieve two-dimensional projections of images and Lloyd-Max Quantization. Is a lossy compression. With a program with pictures. Platform: |
Size: 103424 |
Author:zhrmsl |
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Description: glcm mean in matlab by armin moghimi devloped GLCM_Features1 helps to calculate the features from the different GLCMs
that are input to the function. The GLCMs are stored in a i x j x n
matrix, where n is the number of GLCMs calculated usually due to the
different orientation and displacements used in the algorithm. Usually
the values i and j are equal to NumLevels parameter of the GLCM
computing function graycomatrix(). Note that matlab quantization values
belong to the set {1,..., NumLevels} and not from {0,...,(NumLevels-1)}
as provided in some references
http://www.mathworks.com/access/helpdesk/help/toolbox/images/graycomatrix
.html-glcm mean in matlab by armin moghimi devloped GLCM_Features1 helps to calculate the features from the different GLCMs
that are input to the function. The GLCMs are stored in a i x j x n
matrix, where n is the number of GLCMs calculated usually due to the
different orientation and displacements used in the algorithm. Usually
the values i and j are equal to NumLevels parameter of the GLCM
computing function graycomatrix(). Note that matlab quantization values
belong to the set {1,..., NumLevels} and not from {0,...,(NumLevels-1)}
as provided in some references
http://www.mathworks.com/access/helpdesk/help/toolbox/images/graycomatrix
.html Platform: |
Size: 6144 |
Author:armin |
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Description: 1、用matlab编写采样和量化程序，并对比分析不同空间和幅度分辨率的数字化图像的效果；对比分析自己程序与matlab自带函数的效果；
2、用matlab编写彩色图变灰度图和二值图。-1, using matlab sampling and quantization procedures, and comparative analysis of the effect of different spatial and amplitude resolution digitized image comparative analysis of their own function matlab program and results
2, written in matlab grayscale and color images become binary image. Platform: |
Size: 1448960 |
Author:侯新宇 |
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Description: Implementation of quantization for different images in matlab-Implementation of quantization for different images in matlab Platform: |
Size: 400384 |
Author:irfan khan |
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Description: In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing Map Neural Network. The implemented code, uses RGB and HSV color coding, to perform the clustering task, and user can desired approach of coding.-In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing Map Neural Network. The implemented code, uses RGB and HSV color coding, to perform the clustering task, and user can desired approach of coding. Platform: |
Size: 252928 |
Author:Mustafa |
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Description: Color Reduction and Quantization using k-Means, Fuzzy Clustering (FCM), and SOM Neuarl Network in MATLAB
In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing Map Neural Network. The implemented code, uses RGB and HSV color coding, to perform the clustering task, and user can select desired approach of coding. Platform: |
Size: 248832 |
Author:amardz |
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Search - quantization of images in matlab