fktransform

matlab入门手册，能在短时间内学会基本指令的使用。使用方便，适合初学者(matlab classic instruction set, easy to use query, use namely the investigation, can be started quickly.)

FIR :Transform lowpass filters to bandstop

optical character recognition is used to convert images of any paper into soft copies

选择不同的两个函数做卷积运算，可供选择的函数有矩形窗函数，锯齿波函数和sinc函数，也可自行选择其他窗，观察选取函数的波形。(Choose a different function to do convolution function to choose a rectangular window function, ramp function and the sinc function, to choose the other window, observe the waveform of the selected function.)

以r=6 1 103F为基础，抽取出其他m序列，在生成的m序列集中，寻找出m序列优选对，确定优选对数量，并画出它们自相关和互相关函数图形；(Based on the r = 6 1 103 f, extract other m sequence, concentrated in the generated m sequence, selection to find the m sequence, determine the optimum number of, and draw them autocorrelation and cross-correlation function graph )

通过对数据滤波来进行对静态效应的消噪过程，本代码使用了空间滤波、组合滤波、中值滤波等方法进行对比。(Through data filtering to eliminate noise of static effects of the process, the code uses the spatial filtering, a combination of filtering, median filtering and other methods were compared.)

将低动态范围图像通过色调映射技术转换为高动态范围图像，对图像的亮度通道进行加强，该算法是reinhard代码进行实现的。(The low dynamic range image is transformed into high dynamic range image by hue mapping technology, and the brightness channel of the image is enhanced. The algorithm is implemented by Reinhard code.)

说明：  实现特征波长的提取，连续投影算法可以实现特征光谱信息，结合PCA实现样品分类(Realize the extraction of characteristic wavelength)

维纳噪声抑制，1、 实验原理是利用信号之间的相关性进行信号估计，从而将噪声滤除； 2、 辅助观测信号的噪声抑制可利用Wiener-Hopf方程 求出维纳滤波器的系数 ，式中 是 的自相关阵， 是输入信号 和滤波器输入 之间的互相关矢量； (Wiener noise suppression, 1, experiment is the use of the correlation between the signals for signal estimation, which will filter out the noise 2, the auxiliary noise suppression observed signal Wiener-Hopf equation can be obtained by Wiener filter coefficients, where is the autocorrelation matrix, is the input signal and filters the cross-correlation between the input vector )

Matlab code for following paper> A Deblocking Filter with Two Separate Modes in Block-Based Video Coding IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, VOL. 9, NO. 1, FEBRUARY 1999