双边去噪

图像配准程序，包括角点提取，配对，提纯等操作(image registeration ,including connor detection,match and so on)

应用傅立叶变换对图像处理，实现查看图像的功率谱，以及功率谱经过巴特沃斯高通、低通和高斯高通、低通滤波器后图像的功率谱，再把功率谱还原为图像的功能。(Fourier transform for image processing, see the image of the power spectrum, and the power spectrum after Butterworth high-pass, low-pass and high-pass Gaussian low-pass filter of the image after power spectrum, and then restore the power spectrum of the image.)

说明：  可以读取输出浮点型、整型、复数型影像，对于遥感专业的所有影像读入输出MATLAB中有很大帮助。采用振幅离差阈值提取PS点(Can read floating-point, integer, and complex type of image, for all remote sensing professional images into the MATLAB will be very helpful)

susan实现图像的角点检测,调用的详细说明在源代码内有注释.()

MATLAB实现图像的傅里叶变换，包括一维傅里叶变换，二维傅里叶变换(MATLAB Fourier transform of image, including the one-dimensional Fourier transform, two-dimensional Fourier transform)

SURF算法为SIFT算法的改进，运算速度得到了很大的提高。本资料为基于MATLAB的SURF算法实现，对图像匹配的研究方向会有一定帮助。(SURF algorithm SIFT algorithm, computing speed has been greatly improved. MATLAB based on the information of the SURF algorithm for image matching the direction of the research will certainly help.)

基于MATLAB的数字图像处理程序，给出一幅染色体图像，通过边缘检测，及腐蚀等算法统计出染色体的数量。(MATLAB-based digital image processing procedures, are given a piece of chromosome images, through the edge detection, and corrosion, such as algorithm statistics the number of chromosomes.)

用小波包分析实现轴承故障诊断，信号分析处理，界面编程(Bearing fault diagnosis using wavelet packet analysis and signal analysis and processing, interface programming)

Matlab环境下的几个数字图像处理实验，包含图像灰度变换、直方图均衡化、直方图匹配、邻域平均、局域增强、中值滤波、图像的锐化等(Several digital image processing experiments, including gray transform, histogram equalization, histogram matching, neighborhood average, local increase, median filtering and image sharpening, etc.)

根据RBM深度网络（Hinton，2006）进行MINST手写文字的分类器的训练，利用训练得到的权值制作了这个小程序，通过这个程序可以看出训练结果对数据集内的测试样本和训练样本都能进行很好的识别，但是对其他的手写字体识别就没有那么好了。(According to RBM depth network (Hinton, 2006) conducted MINST handwritten text classifier training, using the training to get the right value to produce this small program, this program can be seen through the results of the training data set and the training sample test samples are can be well identified, but on the other handwriting recognition is not so good.)