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近期成果，与大家分享：奇异值分解、小波降噪、zoom细化 谱峭度 和滤波器设计，共勉(Recent achievements to share with you: singular value decomposition, wavelet noise reduction, zoom refined spectral kurtosis and filter design, encouragement)

从原始图像产生噪声图像，使用db1执行2层小波，使用wpbmpen进行全阈值选择，采用硬阈值和软阈值处理方式,保存低频,进行图像降噪，并绘制各分解系数图像。(Generated noise image from the original image, using db1 wavelet perform two layers using wpbmpen full-threshold selection, using hard threshold and soft threshold approach, saving low frequency, image noise reduction, and draw the decomposition coefficients images.)

说明：  图像识别预处理，用主要用于汽车车牌号识别(Image recognition for license plate recognition)

对理想的心音信号加入噪声，仿真成实际带噪声的心音信号，然后对其进行维纳滤波程序(The ideal heart sound signal added noise, simulation into actual heart sounds with noise signal, and then its Wiener filtering program)

说明：  该文件可以读取MRI raw data，磁共振指的是自旋磁共振（spin magnetic resonance）现象。其意义上较广，包含核磁共振(nuclear magnetic resonance, NMR)、电子顺磁共振（electron paramagnetic resonance, EPR）或称电子自旋共振（electron spin resonance, ESR）(The file can read MRI raw data, Magnetic resonance refers to the phenomenon of spin magnetic resonance. It is broader in meaning and includes nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR) or electron spin resonance (ESR))

【实例简介】本设计为基于MATLAB的火焰烟雾火灾检测系统。传统的采用颜色的方法，误识别大，局限性强。结合火焰是实时动态跳跃的，采用面积增长率，角点和圆形度三个维度相结合的方式判断是否有火焰。该设计测试对象为视频，通过下一帧和上一帧的差异发现是否有火情，并可发出语音报警。本设计带有一个人机交互式GUI界面，界面友好。是个不错的bishe选题。

进行简单的数字图像处理，用MATLAB进行图像旋转，灰度，亮度调节(Perform simple digital image processing)

说明：  实现了图像与视频的信息隐藏，输入图片和视频可进行效果演示(The information hiding of image and video is realized)

说明：  本文以k-means算法为背景，引入信息熵相关知识，从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时，会发生一定的过拟合现象，导致我们得不到预期的聚类数目。本文设计合理的合并准则，令模型简化，有效地消除过拟合现象，使得最后得到的聚类数目与预期符合。，设计合理的准则改进了图像的全自动分割方法，使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.)

ASM算法的matlab实现，完整的ASM算法流程，包含各个子程序(ASM algorithm matlab achieve complete ASM algorithm process contains various subroutines)