/*************************************************************************
*
* \函数名称：
* Canny()
*
* \输入参数:
* unsigned char *pUnchImage- 图象数据
* int nWidth - 图象数据宽度
* int nHeight - 图象数据高度
* double sigma - 高斯滤波的标准方差
* double dRatioLow - 低阈值和高阈值之间的比例
* double dRatioHigh - 高阈值占图象象素总数的比例
* unsigned char *pUnchEdge - canny算子计算后的分割图
*
* \返回值:
* 无
*
* \说明:
* canny分割算子，计算的结果保存在pUnchEdge中，逻辑1(255)表示该点为
* 边界点，逻辑0(0)表示该点为非边界点。该函数的参数sigma，dRatioLow
* dRatioHigh，是需要指定的。这些参数会影响分割后边界点数目的多少
*************************************************************************
*/
void Canny(unsigned char *pUnchImage, int nWidth, int nHeight, double sigma,
double dRatioLow, double dRatioHigh, unsigned char *pUnchEdge)
{
// 经过高斯滤波后的图象数据
unsigned char * pUnchSmooth ;
// 指向x方向导数的指针
int * pnGradX ;
// 指向y方向导数的指针
int * pnGradY ;
// 梯度的幅度
int * pnGradMag ;
pUnchSmooth = new unsigned char[nWidth*nHeight] ;
pnGradX = new int [nWidth*nHeight] ;
pnGradY = new int [nWidth*nHeight] ;
pnGradMag = new int [nWidth*nHeight] ;
// 对原图象进行滤波
GaussianSmooth(pUnchImage, nWidth, nHeight, sigma, pUnchSmooth) ;
// 计算方向导数
DirGrad(pUnchSmooth, nWidth, nHeight, pnGradX, pnGradY) ;
// 计算梯度的幅度
GradMagnitude(pnGradX, pnGradY, nWidth, nHeight, pnGradMag) ;
// 应用non-maximum 抑制
NonmaxSuppress(pnGradMag, pnGradX, pnGradY, nWidth, nHeight, pUnchEdge) ;
// 应用Hysteresis，找到所有的边界
Hysteresis(pnGradMag, nWidth, nHeight, dRatioLow, dRatioHigh, pUnchEdge);
// 释放内存
delete pnGradX ;
pnGradX = NULL ;
delete pnGradY ;
pnGradY = NULL ;
delete pnGradMag ;
pnGradMag = NULL ;
delete pUnchSmooth ;
pUnchSmooth = NULL ;
}
// Canny算子
void Canny(LPBYTE pGray, SIZE sz, double sigma, double dRatLow,
double dRatHigh, LPBYTE pResult)
{
//经过高斯滤波后的图像
LPBYTE pGaussSmooth;
pGaussSmooth = new unsigned char[sz.cx*sz.cy];
//x方向导数的指针
int *pGradX;
pGradX = new int[sz.cx*sz.cy];
//y方向
int *pGradY;
pGradY = new int[sz.cx*sz.cy];
//梯度的幅度
int *pGradMag;
pGradMag = new int[sz.cx*sz.cy];
//对原图高斯滤波
GaussianSmooth(sz,pGray,pGaussSmooth,sigma);
//计算方向导数和梯度的幅度
Grad(sz,pGaussSmooth,pGradX,pGradY,pGradMag);
//应用非最大抑制
NonmaxSuppress(pGradMag,pGradX,pGradY,sz,pResult);
//应用Hysteresis，找到所有边界
Hysteresis(pGradMag,sz,dRatLow,dRatHigh,pResult);
delete[] pGradX;
pGradX = NULL;
delete[] pGradY;
pGradY = NULL;
delete[] pGradMag;
pGradMag = NULL;
delete[] pGaussSmooth;
pGaussSmooth = NULL;
}
bool FGActuator::Run(void )
{
Input = InputNodes[0]->getDoubleValue() * InputSigns[0];
if( fcs->GetTrimStatus() ) initialized = 0;
if (fail_zero) Input = 0;
if (fail_hardover) Input = clipmax*sign(Input);
Output = Input; // Perfect actuator. At this point, if no failures are present
// and no subsequent lag, limiting, etc. is done, the output
// is simply the input. If any further processing is done
// (below) such as lag, rate limiting, hysteresis, etc., then
// the Input will be further processed and the eventual Output
// will be overwritten from this perfect value.
if (fail_stuck) {
Output = PreviousOutput;
} else {
if (lag != 0.0) Lag(); // models actuator lag
if (rate_limit_incr != 0 || rate_limit_decr != 0) RateLimit(); // limit the actuator rate
if (deadband_width != 0.0) Deadband();
if (hysteresis_width != 0.0) Hysteresis();
if (bias != 0.0) Bias(); // models a finite bias
if (delay != 0) Delay(); // Model transport latency
}
PreviousOutput = Output; // previous value needed for "stuck" malfunction
initialized = 1;
Clip();
if (clip) {
saturated = false;
if (Output >= clipmax && clipmax != 0) saturated = true;
else if (Output <= clipmin && clipmin != 0) saturated = true;
}
if (IsOutput) SetOutput();
return true;
}
