求教用C語(yǔ)言實(shí)現(xiàn)低通濾波器

float middle_filter(float middle_value [] , intcount)

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{

float sample_value, data;

int i, j;

for (i=1; i for(j=count-1; j=i,--j){

if(middle_value[j-1]=middle_value[j]{

data=middle_value[j-1];

middle_value[j-1]=middle_value[j]

middle_value[j]=data;

}

}

sample_value=middle_value(count-1)/灶喊稿隱孝滲褲2];

return(sample_value);

}

二階濾波器用C語(yǔ)言怎么寫(xiě)

這個(gè)可比你想象晌大的復(fù)雜多了，s是個(gè)復(fù)變量，1/(s+1)極點(diǎn)在-1，要想用C語(yǔ)言寫(xiě)，必須理解清楚下面幾個(gè)問(wèn)題：

1、輸入必須是個(gè)有限序列，比如(x+yi)，x和y分別是兩個(gè)長(zhǎng)度為N的數(shù)組

2、要過(guò)濾的頻率，必須是個(gè)整型值，或者是個(gè)整型區(qū)間

3、輸出大前結(jié)果同樣是兩個(gè)長(zhǎng)度為N的數(shù)組(p+qi)

4、整個(gè)程宴仿豎序需要使用最基本的復(fù)數(shù)運(yùn)算，這一點(diǎn)C語(yǔ)言本身不提供，必須手工寫(xiě)復(fù)函數(shù)運(yùn)算庫(kù)

5、實(shí)現(xiàn)的時(shí)候具體算法還需要編，這里才是你問(wèn)題的核心。

我可以送你一段FFT的程序，自己琢磨吧，和MATLAB的概念差別很大：

#include assert.h

#include math.h

#include stdio.h

#include stdlib.h

#include string.h

#include windows.h

#include "complex.h"

extern "C" {

// Discrete Fourier Transform (Basic Version, Without Any Enhancement)

// return - Without Special Meaning, constantly, zero

int DFT (long count, CComplex * input, CComplex * output)

{

assert(count);

assert(input);

assert(output);

CComplex F, X, T, W; int n, i;

long N = abs(count); long Inversing = count 0? 1: -1;

for(n = 0; n N ; n++){ // compute from line 0 to N-1

F = CComplex(0.0f, 0.0f); // clear a line

for(i = 0; i N; i++) {

T = input[i];

W = HarmonicPI2(Inversing * n * i, N);

X = T * W;

F += X; // fininshing a line

}//next i

// save data to outpus

memcpy(output + n, F, sizeof(F));

}//next n

return 0;

}//end DFT

int fft (long count, CComplex * input, CComplex * output)

{

assert(count);

assert(input);

assert(output);

int N = abs(count); long Inversing = count 0? -1: 1;

if (N % 2 || N 5) return DFT(count, input, output);

long N2 = N / 2;

CComplex * iEven = new CComplex[N2]; memset(iEven, 0, sizeof(CComplex) * N2);

CComplex * oEven = new CComplex[N2]; memset(oEven, 0, sizeof(CComplex) * N2);

CComplex * iOdd = new CComplex[N2]; memset(iOdd , 0, sizeof(CComplex) * N2);

CComplex * oOdd = new CComplex[N2]; memset(oOdd , 0, sizeof(CComplex) * N2);

int i = 0; CComplex W;

for(i = 0; i N2; i++) {

iEven[i] = input[i * 2];

iOdd [i] = input[i * 2 + 1];

}//next i

fft(N2 * Inversing, iEven, oEven);

fft(N2 * Inversing, iOdd, oOdd );

for(i = 0; i N2; i++) {

W = HarmonicPI2(Inversing * (- i), N);

output[i] = oEven[i] + W * oOdd[i];

output[i + N2] = oEven[i] - W * oOdd[i];

}//next i

return 0;

}//end FFT

void __stdcall FFT(

long N, // Serial Length, N 0 for DFT, N 0 for iDFT - inversed Discrete Fourier Transform

double * inputReal, double * inputImaginary, // inputs

double * AmplitudeFrequences, double * PhaseFrequences) // outputs

{

if (N == 0) return;

if (!inputReal !inputImaginary) return;

short n = abs(N);

CComplex * input = new CComplex[n]; memset(input, 0, sizeof(CComplex) * n);

CComplex * output= new CComplex[n]; memset(output,0, sizeof(CComplex) * n);

double rl = 0.0f, im = 0.0f; int i = 0;

for (i = 0; i n; i++) {

rl = 0.0f; im = 0.0f;

if (inputReal) rl = inputReal[i];

if (inputImaginary) im = inputImaginary[i];

input[i] = CComplex(rl, im);

}//next i

int f = fft(N, input, output);

double factor = n;

//factor = sqrt(factor);

if (N 0)

factor = 1.0f;

else

factor = 1.0f / factor;

//end if

for (i = 0; i n; i++) {

if (AmplitudeFrequences) AmplitudeFrequences[i] = output[i].getReal() * factor;

if (PhaseFrequences) PhaseFrequences[i] = output[i].getImaginary() * factor;

}//next i

delete [] output;

delete [] input;

return ;

}//end FFT

int __cdecl main(int argc, char * argv[])

{

fprintf(stderr, "%s usage:\n", argv[0]);

fprintf(stderr, "Public Declare Sub FFT Lib \"wfft.exe\" \

(ByVal N As Long, ByRef inputReal As Double, ByRef inputImaginary As Double, \

ByRef freqAmplitude As Double, ByRef freqPhase As Double)");

return 0;

}//end main

};//end extern "C"

c語(yǔ)言中值濾波問(wèn)題？

1. 是規(guī)定做中值濾波的早族點(diǎn)不含邊緣塌睜游的點(diǎn)(取決于中值濾波窗口大團(tuán)銷小)。 2,對(duì)圖像邊緣部分的信息進(jìn)行鏡像處理。

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