Description: 《MATLAB 6.5辅助图像处理》
本书是基于MATLAB 6.5的图像处理工具箱v3.2 （Image Processing Toolbox）编写的，较全面系统地介绍了图像处理工具箱v3.2函数在有噪和退化图像的恢复、图形绘制、图像几何变换、图像增强、二值分析、小波分析和分形几何用于图像处理，以及图形用户界面设计等方面的工程实际应用。全书侧重于图像处理工具箱在工程中的具体应用，通过具体的分析和详细的实例，读者不仅可以对MATLAB图像处理工具箱函数的强大功能有一个深刻了解，更能学会正确运用它快速解决实际问题的方法，从而提高分析问题和解决问题的能力。飞思在线http://www.fecit.com.cn“下载专区”提供书中范例源代码。
本书内容全面新颖、针对性强，理论与实际紧密结合，可供从事图像处理相关工作的教师、高年级本科生、研究生和广大科研人员参考。
-"MATLAB 6.5 support image processing," the book is based on MATLAB 6.5 of Image Processing Toolbox v3.2 (Image Processing Toolbox) Prepare, a more comprehensive system to introduce the Image Processing Toolbox v3.2 function in a noisy and the restoration of degraded images, graphics rendering, Image geometry transform, image enhancement, value analysis, wavelet analysis and fractal geometry for image processing, and the graphical user interface design, so the practical application of engineering. The book focused on Image Processing Toolbox works in the concrete application, through specific and detailed analysis of the examples, readers can not only on MATLAB Image Processing Toolbox function of the powerful have a deep understanding, better learn how to correctly apply it quick Platform: |
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Author:xinxin |
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Description: 利用小波分解与重构,实现图像增强和融合,可灵活选用其他小波,简单易懂,特别适合小波初学者.-using wavelet decomposition and reconstruction, image enhancement and integration, the flexibility to choose other wavelet is simple to understand and Wavelet particularly suitable for beginners. Platform: |
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Author:whq |
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Description: 小波工具箱的应用基础 395
16.1 一维小波分析的应用 395
16.1.1 小波分解在普通信号分析中的应用 395
16.1.2 小波变换在信号特征检测中的应用 411
16.2 二维小波分析的应用 417
16.2.1 小波分析在图像平滑中的应用 417
16.2.2 小波分析在图像增强中的应用 418
16.2.3 小波分析在图像融合中的应用 420
16.3 小波包分析的应用 422
16.3.1 小波包在信号时频分析中的应用 423
16.3.2 小波包在图像边缘检测中的应用 429-toolbox of 16.1 basis of a 395-dimensional wavelet analysis of 395 small 16.1.1 Decomposition of the ordinary wave signal analysis of 395 16.1.2 wavelet transform in signal detection of 41 a 16.2 2D wavelet analysis of 417 16.2.1 wavelet analysis in image smoothing of 417 1 6.2.2 wavelet analysis in image enhancement of 418 16.2.3 wavelet analysis in Image Fusion System 420 16.3 wavelet packet analysis of wavelet packet Entry 422 in the signal frequency analysis of 42 3 16.3.2 wavelet packet in Edge Detection of 429 Platform: |
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Author:崔鹏 |
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Description: 在课程设计中，利用小波变换实现了医学图象对比度的增强-in curriculum design, the use of wavelet transform of the medical image contrast enhancement Platform: |
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Author:lipei |
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Description: 适合初学小波的同志，小波图像增强原理底层。严格高低频分解重构，没有使用小波工具库。-Suitable for beginners wavelet comrades, the underlying principle of wavelet image enhancement. Strict high-low-frequency decomposition of reconstruction, did not use the wavelet tool library. Platform: |
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Author:bailinshu |
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Description: 通过小波变换以实现去除图像噪声和对图像进行增强的程序，效果很好。-Through the wavelet transform in order to achieve removal of image noise and image enhancement procedures, the effect of good. Platform: |
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Author:sh85 |
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Description: 图象增强
小波变换将一幅图象分解为大小、位置和方向都不同的分量。在做逆变换之前可以改变小波变换域中某些系数的大小，这样就能够洋选择的放大所感兴趣的分量而减小不需要的分量。
给定一个图象信号，用二维小波分析对图象进行增强处理。-Image enhancement will be a wavelet transform image decomposition for size, location and direction of the weight is different. To do before the inverse transform of wavelet transform domain can change the size of certain coefficients, so that foreigners will be able to choose to enlarge the amount of interest and reduce the unwanted weight. Given an image signal, using two-dimensional wavelet analysis of images to enhance treatment. Platform: |
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Author:eels |
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Description: 小波变换在图像处理中的应用，包括不同类型图像间的转换，二维小波对图像进行小波去噪，二维小波进行图像压缩，利用小波分析对二维含噪图像去噪，二维小波利用中值滤波对图像进行平滑，小波分析进行图像增强，小波分析对两个不同的图像进行融合-Wavelet transform in image processing applications, including different types of image inter-conversion, two-dimensional wavelet image wavelet denoising, two-dimensional wavelet image compression, the use of wavelet analysis of two-dimensional noisy image denoising, the use of two-dimensional wavelet median filter for image smoothing, wavelet analysis for image enhancement, wavelet analysis of two different image fusion Platform: |
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Author:fuhuaizheng |
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Description: 本文研究了基于小波变换的几何信息特性和变分问题的图像分解改进算法，实现Contourlet变换和小波变换相结合的图像增强改进算法。表明改进算法在增强有用信号的同时较大限度地抑制图像噪声。-This paper studies the geometric features based on wavelet transform and variational image decomposition improved algorithm Contourlet transform and wavelet transform combination of image enhancement to improve algorithm. That improved algorithm to a large extent to suppress image noise at the same time enhance the useful signal. Platform: |
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Author:白青 |
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Description: 下载并读入被噪音污染的Noisychurch图像数据，用Matlab 编程采用下述方法分
别实现该图像的增强操作：
1） 用空域法实现图像的增强，分别采用如下模板操作：2x2 和3x3 的幅值为1
的模板，比较去噪和模糊的折中效果；采用3x3 的中值滤波器进行去噪操作；
采用Laplacian 模板[0 -1 0 -1 5 -1 0 -1 0]进行锐化操作。
2） 用频域法实现该图像的低通和高通滤波，选择合适的截止频率。
3） 用小波分析法实现该图像的低通和高通滤波，注意离散小波分析的分解和重
构算法的运用。
4） 比较上述三种处理方法的结果。 -Download and read by the noise pollution Noisychurch image data using Matlab programming using the following method to achieve the image enhancement operation: 1) image enhancement airspace law, respectively, using the following template operation: 2x2 and 3x3 amplitude a template comparison denoising and fuzzy compromise denoising operation with a 3x3 median filter using Laplacian template [0-10 -15-1 0-10] for sharpening operation. . 2) low-pass and high-pass filtering of the image using the frequency-domain method, select the appropriate cut-off frequency. 3) low-pass and high-pass filtering of the image using wavelet analysis, pay attention to the use of discrete wavelet analysis decomposition and reconstruction algorithm. 4) comparing the results of the three processing method. Platform: |
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Author:Haibin Zhang |
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Description: 针对基于小波变换的红外图像增强方法视觉效果不够理想的缺点, 提出了一种基于平稳小波变换和Retinex 的红外图像增强方法, 利用Retinex 增强算法增强图像的视觉效果, 并改善其亮度均匀性。首先, 对红外图像经平稳小波变换后的最大尺度低频子带图像进行多尺度Retine x 增强 然后, 利用贝叶斯萎缩阈值法对高频子带图像进行阈值去噪, 并根据低频子带图像的局部对比度和模糊规则计算高频子带的增益系数, 从而得到增强后的高频子带图像 最后, 由低频子带图像和高频子带图像重构得到增强后的图像。针对大量图像进行了实验和增强效果的定性与定量评价, 并与双向直方图均衡法、二代小波变换法、Curvelet 变换法和多尺度Retinex法作了比较。结果表明, 所提出的方法增强了图像细节, 抑制了噪声, 并明显改善了图像的整体视觉效果。-As infrared image enhancement method based on wavelet transformation has the problem of unperfect visual effect , and Retinex enhancement algorithm can enhance visual effect of the image by improving brightness uniformity , amethod based on stationary wavelet transformation and Retinexis proposed.Firstly , the infrared image is decomposed into high-frequency detail and low-frequency approximation components at various resolutions, and the low frequency subband image of the largest scale is enhanced by multiscale Retinex algorithm.Then, the highfrequency subband images are denoised by Bayesian shrinkage method, and the gain coefficients of high-frequency subbands are available by calculating the local contrast of the enhanced low-frequency subband based on fuzzy rules to get the enhanced high-frequency subband images .Finally, the enhanced image is reconstructed by the low-frequency subband and high-frequency subbands .Experiments with qualitative and quantitative uation are carried ou Platform: |
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Author:kiel |
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Search - wavelet image enhancement