explam-fft

对图像进行二值化处理的源代码，编译后的可执行文件须带参数运行),非常好的代码.欢迎使用和下载!呵呵,真的,不信下下看啊!(two pairs of images of the value of the source code, compile the executable files carry parameters run), very good code. welcome to download and use! Oh, really, do not look at the next letter ah!)

基于离散余弦变换的数字水印，包括水印的嵌入和提取以及常间的各种水印攻击(Discrete cosine transform based on digital watermarking, including the watermark embedding and extraction, as well as between the various watermark attacks often)

一个散焦模糊自动复原的算法，自动估计散焦半径，在频率域识别参数，并用最小二乘滤波复原(A defocus blur automatic recovery algorithm automatically estimated defocus radius, in the frequency domain identification parameters, and by the least squares filter restoration )

快速运动去模糊，在盲去卷积过程中运用一些加速算法(Fast motion to blur in the blind deconvolution algorithm to accelerate the process of using some)

基于互信息的图像配准源代码，，采用粒子群优化算法可直接使用。 (Based on mutual information image registration source code, using particle swarm optimization algorithm can be used directly.)

基于MALTAB实现的舌象纹理特征提取，程序不大但是使用(ongue like texture feature extraction matlab implementation tongue like texture feature extraction matlab implementation)

This program contains some basic image processing things, such as: 256 colors to grayscale, contrast stretching, anti-color, brightness change, etc.

用于植物叶片分类的图形界面,是Matlab源码，用BP神经网络实现(For plant leaf classification graphical interface, the Matlab source code, using BP neural network)

根据论文Harris C. A combined corner and edge detector[J]. Proc Alvey Vision Conf, 1988, 1988(3):147-151实现Harris角点检测(Harris corner detection)

针对CT 医学图像和MR I 医学图像成像特点, 提出了基于快速整数提升小波变换的融合方法。在CT 和 MR I 两幅医学图像配准的前提下, 利用提升小波变换把图像分解成低频和高频子图像, 对于小波变换后的高频 子图像, 选择区域标准差大的作为融合后的子图像 对于低频子图像, 采用加权融合, 最后进行小波逆变换, 得到 融合后的图像, 并对融合后图像用信息熵、平均梯度、相关系数的指标进行评价。实验结果表明, 基于快速整数提 升小波变换融合中, 小波高低频系数采用不同的规则能够取得更好的融合效果, 其轮廓清晰。该算法能够提升融 合后的医学图像信息量, 同时有效地保护图像的细节信息, 在执行时间和图像质量上均优于普通小波算法。(A imed at the characterist ics of CT andMR Imedical images, a new image fu sion al2 go rithm based on the fast in t lif t ing w avelet t ran sfo rm s is p ropo sed. Two o riginal images are decompo sed by the fast in t lif t ing w avelet t ran sfo rm s. The fu sion ru le based on the max imum standard deviat ion value variance is u sed to fu se the h igh f requency sub2image, w h ile a w eigh t2 ed average fu sed ru le is app lied by coeff icien t s of the low f requency. F inally, the fu sion image is recon st ructed fo r perfo rm ing inverse fast in t lif t ing w avelet t ran sfo rm s. The fu sion image is evaluated by en t ropy, average gradien t, and co rrelat ion coeff icien t s. Experimen tal resu lt show s that the fu sion image hasmo re info rmat ion than o riginal images and imp roves the quali2 ty of o riginal images. M eanw h ile, the fu sion image p ro tect s detail characterist ics of the image, thu s the real2t ime p rocess and image qualit ies are w ell than tha)