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傅立叶变换，等距离采样，等角度采样，轮廓提取，形态处理(Fourier transform, equidistant sampling, in terms of sampling, contour extraction, morphological processing)

小波学习资料 供初学者和小波爱好者参考用()

自适应的直方图均衡化程序（AHE），用于图像增强(Adaptive histogram equalization program)

MATLAB实现图像纹理特征提取：自相关函数法、灰度共生矩阵、分数阶傅里叶变换。GUI界面。运行后可自定义自相关函数的x和y轴偏移，灰度共生矩阵的距离和角度，分数阶傅里叶变换的阶数。输出相应的特征图。(MATLAB realize image texture feature extraction: autocorrelation function method, gray co-occurrence matrix, fractional Fourier transform. GUI interface. After operation, the X and Y axis shifts of the correlation function, the distance and the angle of the GLCM, and the order of the fractional Fu Liye transform can be defined. Output the corresponding feature map.)

区域生长算法分割脑部图像， 两个种子点，解决完整分割白质的算法(Region growing algorithm for segmentation of brain images, the two seed points, solve the integrity of white matter segmentation algorithm)

里面包含kalman，扩展kalman，无迹kalman，粒子滤波，无迹粒子滤波等源码的实现。(upf--The Unscented Particle Filter )

实验目的： 1） 图像水平集合 2） 图像加密算法 3） 边缘提取 4） 噪音图像的产生 （2）显示图像，理解图像的模型 （3）使用图像的不同格式，理解图像压缩的意义 （4）对图像做简单的操作 本次实验需要熟练使用以下几个MATLAB命令： imread, imwrite, imshow,figure (Experimental purposes: 1) the level of collection of image 2) image encryption algorithm 3) Edge 4) noise generated images (2) display images, understanding image model (3) the use of images in different formats, understanding the significance of image compression (4) image to do a simple experiment needs to operate the skilled use of the following MATLAB command: imread, imwrite, imshow, figure)

一种基于DCT变换的数字水印算法的实现过程,水印为伪随机序列，包括嵌入和提取两个过程。其中textmark.m为攻击实验代码。(DCT-based Digital Watermarking Algorithm Transform realize the process, the watermark for the pseudo-random sequence, including both the process of embedding and extraction. Textmark.m experiment in which the attack code.)

利用多尺度高斯函数去除场景的光照分量；然后构造了一种二维伽马函数，利用光照分量的分布特性调整二维伽马函数的参数，降低光照过强区域的亮度值，提高光照过暗区域的亮度值，最终实现对光照不均匀图像的自适应校正处理。(The multi scale Gauss function is used to remove the illumination component of the scene, and then a two-dimensional gamma function is constructed. The parameters of the two-dimensional gamma function are adjusted by the distribution characteristics of the illumination component, the brightness value of the light illuminated region is reduced and the brightness value of the light dark area is improved. Finally, the adaptive correction of the uneven illumination image is realized. Positive treatment.)

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