WaveletTransform

一个matlab小程序，用来将tif序列图片转换成envi可读取的raw文件(A matlab applet for converting TIF sequence images into envi readable raw files)

一篇关于光声成像的图像重建算法研究，开发工具为matlab，罗列了很多理论知识(A photoacoustic imaging of image reconstruction algorithms, development tools matlab, listed a lot of theoretical knowledge )

多波段图像融合的一个实例，matlab编写。(Multi-band image fusion an example, matlab prepared.)

图像分类程序，此图像分类采用 SIFT + Kmeans 聚类的方法，然后调用 MLP 对其特征进行分类处理，速度实现比较快，正确率高(Image classification procedures, the use of this image classification method SIFT+ Kmeans clustering, and then call the MLP classification of its features, faster speed to achieve the correct rate)

基于matlab的色差图像分割程序，可以实现复杂背景下的图像分割。(Matlab based on the color image segmentation procedure, the complexity can be achieved in the context of image segmentation.)

五种粒子滤波仿真，便于初学者学习粒子滤波算法(Five particle filter simulation, easy for beginners to learn particle filter)

基于统计算法的红外图像非均匀性矫正算法，场景类算法，实现实时校正(IRFPA NUC)

说明：  Donoho提出的小波阀值去噪的基本思想是将信号通过小波变换（采用Mallat算法）后，信号产生的小波系数含有信号的重要信息，将信号经小波分解后小波系数较大，噪声的小波系数较小，并且噪声的小波系数要小于信号的小波系数，通过选取一个合适的阀值，大于阀值的小波系数被认为是有信号产生的，应予以保留，小于阀值的则认为是噪声产生的，置为零从而达到去噪的目的。尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点。(The basic idea of wavelet threshold de-noising proposed by Donoho is that the wavelet coefficients generated by the signal after passing through the wavelet transform (Mallat algorithm) contain the important information of the signal. After the wavelet decomposition, the wavelet coefficients of the signal are larger, the wavelet coefficients of the noise are smaller, and the wavelet coefficients of the noise are smaller than the wavelet coefficients of the signal. By selecting a suitable threshold, the wavelet coefficients of the noise are larger than the valve The wavelet coefficients of values are considered to be generated by signals, which should be preserved. The ones less than the threshold are considered to be generated by noise, which is set to zero to achieve the purpose of denoising.)

说明：  内窥镜图像的细节增强和亮度增强算法，适用于胃部图像处理(Endoscopic image detail enhancement and brightness enhancement algorithm for stomach image processing)

c++语言或MATLAB编程对256×256的灰度图像进行8×8DCT变换，对变换后的结果进行处理： 采用区域编码和阈值编码方法实现图像压缩，保留 50％ 的系数(区域编码保留前 50%个系数，阈值编码保留 50%的大系数）； 再反变换后，对比原始图像和处理后的图像。(C++ or MATLAB programming performs 8 * 8DCT transform on 256 * 256 grayscale images, processing the transformed results: The region coding and threshold coding are used to compress the image, and the coefficient of 50% is retained (the first 50% coefficients are reserved for the region code and the large coefficient of the threshold code is retained by 50%). After inverse transformation, the original image and the processed image are compared.)