Depth-map-extraction

能够实现对生物芯片的识别和图像处理，识别有效芯片区域，读取阴性和阳性点分布和数量。(It can realize the recognition and image processing of biochip, identify the effective chip area, read the distribution and number of negative and positive points.)

对于传统去噪模型的大幅改进，之前的模型都会出现阶梯效应的现象，采取了新的模型对图像进行建模，有效改善了图像去噪图像修复等过程中引入的阶梯效应，而且一定程度上对于图像纹理的修复也有很大的作用(For significantly improve the traditional de-noising model, the model will appear before the phenomenon of the staircase effect, to take a new model for image modeling, effectively improved the staircase effect denoising image restoration process introduced, and to a certain extent for texture of repair also has a significant role)

说明：  小波分析增强滤波。小波变换的原理类似傅里叶变换，只是把三角函数基换成了小波基。与傅里叶变换不同，小波变换有两个变量：scale和translation。scale控制小波函数的收缩，其导数即为频率，translation控制小标函数的平移，平移量对应时间。通过信号的伸缩平移，可以得到某种重合情况，这样积分也会得到一个极大值，不同的是，得到频率成分的同时，还可以知道该频率的时间位置。(Wavelet analysis enhances filtering.The wavelet transform works like the Fourier transform, except that the trigonometric basis is replaced by a wavelet basis. Unlike the Fourier transform, the wavelet transform has two variables: scale and Translation. Scale controls the contraction of the wavelet function, its derivative is frequency, translation controls the translation of the small scale function, and the translation corresponds to the time. By stretching and shifting the signal, you can get some kind of coincidence, so that the integral will also get a maximum, but the difference is that when you get the frequency component, you can also know the time position of that frequency.)

双树复小波变换的图像融合程序代码，有图可编译运行(DTCWT image fusion)

智能算法实现图像分割，读取一张黑白图片进行阈值分割。(Intelligent algorithms for image segmentation, read a black and white image thresholding.)

可以动态调节运行环境的参数，重要参数的提取，利用自然梯度算法。( Can dynamically adjust the parameters of the operating environment, Extract important parameters, Use of natural gradient algorithm.)

本书第一部分主要介绍机器学习基础，以及如何利用算法进行分类，并逐步介绍了多种经典的监督学习算法，如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树（CART）算法等。第三部分则重点介绍无监督学习及其一些主要算法：k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。 全书通过精心编排的实例，切入日常工作任务，摒弃学术化语言，利用高效的可复用Python代码来阐释如何处理统计数据，进行数据分析及可视化。通过各种实例，...( U672C u4E66 u7B2C u4E00 u90E8 u5206 u5206 u4E3B u8991 u4ECB u7ECD u673A u5668 u5B66 u4E60 u57FA u7840 uFF0C u4EE5 u53CA u5982 u4F55 u5229 u7528 u7B97 u6CD5 U8FDB u883C u5206 u7C7B uFF0C u5E76 u9010 u6B65 u4ECB u7ECD u4E86 u591A U90BB u6CD2 u3001 u6734 u7D2 u8D1D u53F6 u65AF u7B97 u6CD5 u3001Logistic u56DE u5F52 u7B97 u6CD5 u3001 u652F u6301 u5411 u91CF u673A u3001AdaBoost u96C6 u6210 U65B9 u6CD5 u3001 u57FA u4E8E u6811 u7R4 u5F52 u7B97 u6CD2 u5286 u5206 u7C7B u56DE u5F52 u6811 uFF08CART uFF09 u7B97 u6CD5 u7B49 u3002 u7B2C u4E09 U90E8 u5209 u5109 u91A u0312 u4E9B u8E1B u8981 u7B97 u6CD5 uFF1Ak u5747 u503C u805A u7B7B U7B97 u6CD3 u30011 by default for uppercase and uupstr U4E9B u9644 u5C5E u5DE5 u5177 u3002 u5168 u4E66 u901A u8FC7 u7CBE U5FC3 u7396 u7392 u7B09 u5B09 u5B09 u5B09 u5B03 U7528 u9184 u5R4 u5904 u7403 u7R03 u7 U5206 u6790 u53CA u53EF u89)

本程序实现Bilateral滤波，以实现边缘保留的平滑处理，同时可用于灰度及彩色图像。(Bilateral filtering realize this procedure in order to achieve a smooth edge to retain the handle at the same time can be used for gray and color images.)

数字图像处理第二版中文版（冈萨雷斯）Digital Image Processing(Digital Image Processing 2nd Edition Chinese (Gonzalez))

用MATLAB编写的粒子滤波器程序，能很好对目标进行跟踪，适合学习粒子滤波器的同学。(Particle filter program written using MATLAB, well target tracking, suitable for students learning particle filter.)