资源列表
global-threshold-denoising-1
- 小波图像去噪，全局阈值法，是多阈值小波去噪中两大部分：全局阈值法玉局部阈值法的重要组成部分。-Wavelet denoising, the global threshold method, the multi-threshold wavelet de-noising of two parts: the global threshold method jade local threshold an important part of the law.
zxw
- 简单的画图软件，可以用直线，曲线，填充矩形，填充椭圆等等。-Simple drawing software, you can use straight lines, curves, filled rectangle, fill an ellipse.
PCA
- PCA 很好用的一套程序 对于故障诊断和人脸识别有很好的效果-PCA good set of procedures for fault diagnosis and recognition of good results
image-process-system
- 利用c++语言编写，将图像增强，图像几何变换，图像正交变换，图像分割等功能集成于一个系统。-To use c++ language, image enhancement, image geometric transformation, image orthogonal transform, image segmentation, and other functions into one system.
LDWT_SIFT
- 提供一种小波和sift混合处理图像的一种新算法的代码，对于尺度变换具有更好的不变性-A new algorithm of a wavelet and sift blending image code for the scale transformation has better invariance
demo_ASIFT_src
- 提供一种改进的sift算法，即asift算法的实现代码，代码效率高。-Provide an improved sift algorithm, namely asift algorithm code, the code efficiency is high.
MSER_matlab
- 经典图像处理算法，即仿射不变算法mser的仿真代码，用于分析其算法的有效性。-The classical image processing algorithms, affine invariant algorithm mser simulation code used to analyze the effectiveness of their algorithm.
CepstrumPWiner
- 针对散焦模糊图像，用matlab实现了先基于倒谱相关性对PSF的参数估计，再用维纳滤波实现复原的算法。-Defocus blurred image using matlab first estimated based on the parameters of the cepstrum on PSF, and then the Wiener filter recovery algorithm.
OpenCV-program-
- 提供给初学者一些经典的opencv源代码，包含很多方向的内容，代码可读性高。-Available to beginners some classic opencv source code contains a lot of direction, readable code.
opencv-dwt
- 小波变换是图像处理中一种有效的变换方法，提供利用opencv实现的小波变换代码-The wavelet transform is an effective transformation method in image processing, opencv realized wavelet transform code
tupianchuli
- 图片处理实现缩放、旋转、灰度变换、直方图均衡化-Image processing to achieve scale, rotation, gray level transformation, histogram equalization
wavelet
- 小波分析与重构，清华大学精品讲解，不看会后悔的。-Wavelet analysis and reconstruction, Tsinghua University, boutique explanation, do not look at will regret it.