ximadsp.cpp

It s a tool designed to extract as much information as possible from Bluetooth devices without the r

	/* converting from double to byte, there is a HUGE loss in the dynamics
	  "nn" tries to keep an acceptable SNR, but 8bit=48dB: don't ask more */
	double nn=pow((double)2,(double)log((double)max(w,h))/(double)log((double)2)-4);
	//reversed gain for reversed transform
	if (direction==-1) nn=1/nn;
	//bMagnitude : just to see it on the screen
	if (bMagnitude) nn*=4;

	for (j=0;j<h;j++) {
		for (k=0;k<w;k++) {
			if (bMagnitude){
				tmpReal->SetPixelIndex(k,j,(BYTE)max(0,min(255,(nn*(3+log(_cabs(grid[k][j])))))));
				if (grid[k][j].x==0){
					tmpImag->SetPixelIndex(k,j,(BYTE)max(0,min(255,(128+(atan(grid[k][j].y/0.0000000001)*nn)))));
				} else {
					tmpImag->SetPixelIndex(k,j,(BYTE)max(0,min(255,(128+(atan(grid[k][j].y/grid[k][j].x)*nn)))));
				}
			} else {
				tmpReal->SetPixelIndex(k,j,(BYTE)max(0,min(255,(128 + grid[k][j].x*nn))));
				tmpImag->SetPixelIndex(k,j,(BYTE)max(0,min(255,(128 + grid[k][j].y*nn))));
			}
		}
	}

	for (k=0;k<w;k++) free (grid[k]);
	free (grid);

	if (srcReal==0 && dstReal==0) delete tmpReal;
	if (srcImag==0 && dstImag==0) delete tmpImag;

	return true;
}
////////////////////////////////////////////////////////////////////////////////
bool CxImage::IsPowerof2(long x)
{
	long i=0;
	while ((1<<i)<x) i++;
	if (x==(1<<i)) return true;
	return false;
}
////////////////////////////////////////////////////////////////////////////////
/**
   This computes an in-place complex-to-complex FFT 
   x and y are the real and imaginary arrays of n=2^m points.
   o(n)=n*log2(n)
   dir =  1 gives forward transform
   dir = -1 gives reverse transform 
   Written by Paul Bourke, July 1998
   FFT algorithm by Cooley and Tukey, 1965 
*/
bool CxImage::FFT(int dir,int m,double *x,double *y)
{
	long nn,i,i1,j,k,i2,l,l1,l2;
	double c1,c2,tx,ty,t1,t2,u1,u2,z;

	/* Calculate the number of points */
	nn = 1<<m;

	/* Do the bit reversal */
	i2 = nn >> 1;
	j = 0;
	for (i=0;i<nn-1;i++) {
		if (i < j) {
			tx = x[i];
			ty = y[i];
			x[i] = x[j];
			y[i] = y[j];
			x[j] = tx;
			y[j] = ty;
		}
		k = i2;
		while (k <= j) {
			j -= k;
			k >>= 1;
		}
		j += k;
	}

	/* Compute the FFT */
	c1 = -1.0;
	c2 = 0.0;
	l2 = 1;
	for (l=0;l<m;l++) {
		l1 = l2;
		l2 <<= 1;
		u1 = 1.0;
		u2 = 0.0;
		for (j=0;j<l1;j++) {
			for (i=j;i<nn;i+=l2) {
				i1 = i + l1;
				t1 = u1 * x[i1] - u2 * y[i1];
				t2 = u1 * y[i1] + u2 * x[i1];
				x[i1] = x[i] - t1;
				y[i1] = y[i] - t2;
				x[i] += t1;
				y[i] += t2;
			}
			z =  u1 * c1 - u2 * c2;
			u2 = u1 * c2 + u2 * c1;
			u1 = z;
		}
		c2 = sqrt((1.0 - c1) / 2.0);
		if (dir == 1)
			c2 = -c2;
		c1 = sqrt((1.0 + c1) / 2.0);
	}

	/* Scaling for forward transform */
	if (dir == 1) {
		for (i=0;i<nn;i++) {
			x[i] /= (double)nn;
			y[i] /= (double)nn;
		}
	}

   return true;
}
////////////////////////////////////////////////////////////////////////////////
/**
   Direct fourier transform o(n)=n^2
   Written by Paul Bourke, July 1998 
*/
bool CxImage::DFT(int dir,long m,double *x1,double *y1,double *x2,double *y2)
{
   long i,k;
   double arg;
   double cosarg,sinarg;
   
   for (i=0;i<m;i++) {
      x2[i] = 0;
      y2[i] = 0;
      arg = - dir * 2.0 * PI * i / (double)m;
      for (k=0;k<m;k++) {
         cosarg = cos(k * arg);
         sinarg = sin(k * arg);
         x2[i] += (x1[k] * cosarg - y1[k] * sinarg);
         y2[i] += (x1[k] * sinarg + y1[k] * cosarg);
      }
   }
   
   /* Copy the data back */
   if (dir == 1) {
      for (i=0;i<m;i++) {
         x1[i] = x2[i] / m;
         y1[i] = y2[i] / m;
      }
   } else {
      for (i=0;i<m;i++) {
         x1[i] = x2[i];
         y1[i] = y2[i];
      }
   }
   
   return true;
}
////////////////////////////////////////////////////////////////////////////////
/**
 * Combines different color components into a single image
 * \param r,g,b: color channels
 * \param a: alpha layer, can be NULL
 * \param colorspace: 0 = RGB, 1 = HSL, 2 = YUV, 3 = YIQ, 4 = XYZ 
 * \return true if everything is ok
 */
bool CxImage::Combine(CxImage* r,CxImage* g,CxImage* b,CxImage* a, long colorspace)
{
	if (r==0 || g==0 || b==0) return false;

	long w = r->GetWidth();
	long h = r->GetHeight();

	Create(w,h,24);

	g->Resample(w,h);
	b->Resample(w,h);

	if (a) {
		a->Resample(w,h);
#if CXIMAGE_SUPPORT_ALPHA
		AlphaCreate();
#endif //CXIMAGE_SUPPORT_ALPHA
	}

	RGBQUAD c;
	for (long y=0;y<h;y++){
		info.nProgress = (long)(100*y/h); //<Anatoly Ivasyuk>
		for (long x=0;x<w;x++){
			c.rgbRed=r->GetPixelIndex(x,y);
			c.rgbGreen=g->GetPixelIndex(x,y);
			c.rgbBlue=b->GetPixelIndex(x,y);
			switch (colorspace){
			case 1:
				SetPixelColor(x,y,HSLtoRGB(c));
				break;
			case 2:
				SetPixelColor(x,y,YUVtoRGB(c));
				break;
			case 3:
				SetPixelColor(x,y,YIQtoRGB(c));
				break;
			case 4:
				SetPixelColor(x,y,XYZtoRGB(c));
				break;
			default:
				SetPixelColor(x,y,c);
			}
#if CXIMAGE_SUPPORT_ALPHA
			if (a) AlphaSet(x,y,a->GetPixelIndex(x,y));
#endif //CXIMAGE_SUPPORT_ALPHA
		}
	}

	return true;
}
////////////////////////////////////////////////////////////////////////////////
/**
 * Smart blurring to remove small defects, dithering or artifacts.
 * \param radius: normally between 0.01 and 0.5
 * \param niterations: should be trimmed with radius, to avoid blurring should be (radius*niterations)<1
 * \param colorspace: 0 = RGB, 1 = HSL, 2 = YUV, 3 = YIQ, 4 = XYZ 
 * \return true if everything is ok
 */
bool CxImage::Repair(float radius, long niterations, long colorspace)
{
	if (!IsValid()) return false;

	long w = GetWidth();
	long h = GetHeight();

	CxImage r,g,b;

	r.Create(w,h,8);
	g.Create(w,h,8);
	b.Create(w,h,8);

	switch (colorspace){
	case 1:
		SplitHSL(&r,&g,&b);
		break;
	case 2:
		SplitYUV(&r,&g,&b);
		break;
	case 3:
		SplitYIQ(&r,&g,&b);
		break;
	case 4:
		SplitXYZ(&r,&g,&b);
		break;
	default:
		SplitRGB(&r,&g,&b);
	}
	
	for (int i=0; i<niterations; i++){
		RepairChannel(&r,radius);
		RepairChannel(&g,radius);
		RepairChannel(&b,radius);
	}

	CxImage* a=NULL;
#if CXIMAGE_SUPPORT_ALPHA
	if (AlphaIsValid()){
		a = new CxImage();
		AlphaSplit(a);
	}
#endif

	Combine(&r,&g,&b,a,colorspace);

	delete a;

	return true;
}
////////////////////////////////////////////////////////////////////////////////
bool CxImage::RepairChannel(CxImage *ch, float radius)
{
	if (ch==NULL) return false;

	CxImage tmp(*ch);
	if (!tmp.IsValid()) return false;

	long w = ch->GetWidth()-1;
	long h = ch->GetHeight()-1;

	double correction,ix,iy,ixx,ixy,iyy,den,num;
	int x,y,xy0,xp1,xm1,yp1,ym1;
	for(x=1; x<w; x++){
		for(y=1; y<h; y++){

			xy0 = ch->GetPixelIndex(x,y);
			xm1 = ch->GetPixelIndex(x-1,y);
			xp1 = ch->GetPixelIndex(x+1,y);
			ym1 = ch->GetPixelIndex(x,y-1);
			yp1 = ch->GetPixelIndex(x,y+1);

			ix= (xp1-xm1)/2.0;
			iy= (yp1-ym1)/2.0;
			ixx= xp1 - 2.0 * xy0 + xm1;
			iyy= yp1 - 2.0 * xy0 + ym1;
			ixy=(ch->GetPixelIndex(x+1,y+1)+ch->GetPixelIndex(x-1,y-1)-
				 ch->GetPixelIndex(x-1,y+1)-ch->GetPixelIndex(x+1,y-1))/4.0;

			num= (1.0+iy*iy)*ixx - ix*iy*ixy + (1.0+ix*ix)*iyy;
			den= 1.0+ix*ix+iy*iy;
			correction = num/den;

			tmp.SetPixelIndex(x,y,(BYTE)min(255,max(0,(xy0 + radius * correction))));
		}
	}

	for (x=0;x<=w;x++){
		tmp.SetPixelIndex(x,0,ch->GetPixelIndex(x,0));
		tmp.SetPixelIndex(x,h,ch->GetPixelIndex(x,h));
	}
	for (y=0;y<=h;y++){
		tmp.SetPixelIndex(0,y,ch->GetPixelIndex(0,y));
		tmp.SetPixelIndex(w,y,ch->GetPixelIndex(w,y));
	}
	ch->Transfer(tmp);
	return true;
}
////////////////////////////////////////////////////////////////////////////////
/**
 * Enhance the variations between adjacent pixels.
 * Similar results can be achieved using Filter(),
 * but the algorithms are different both in Edge() and in Contour().
 * \return true if everything is ok
 */
bool CxImage::Contour()
{
	if (!pDib) return false;

	long Ksize = 3;
	long k2 = Ksize/2;
	long kmax= Ksize-k2;
	long i,j,k;
	BYTE maxr,maxg,maxb;
	RGBQUAD pix1,pix2;

	CxImage tmp(*this,pSelection!=0,true,true);
	if (!tmp.IsValid()) return false;

	long xmin,xmax,ymin,ymax;
	if (pSelection){
		xmin = info.rSelectionBox.left; xmax = info.rSelectionBox.right;
		ymin = info.rSelectionBox.bottom; ymax = info.rSelectionBox.top;
	} else {
		xmin = ymin = 0;
		xmax = head.biWidth; ymax=head.biHeight;
	}

	for(long y=ymin; y<ymax; y++){
		info.nProgress = (long)(100*y/head.biHeight);
		if (info.nEscape) break;
		for(long x=xmin; x<xmax; x++){
#if CXIMAGE_SUPPORT_SELECTION
			if (SelectionIsInside(x,y))
#endif //CXIMAGE_SUPPORT_SELECTION
				{
				pix1 = GetPixelColor(x,y);
				maxr=maxg=maxb=0;
				for(j=-k2, i=0;j<kmax;j++){
					for(k=-k2;k<kmax;k++, i++){
						pix2=GetPixelColor(x+j,y+k);
						if ((pix2.rgbBlue-pix1.rgbBlue)>maxb) maxb = pix2.rgbBlue;
						if ((pix2.rgbGreen-pix1.rgbGreen)>maxg) maxg = pix2.rgbGreen;
						if ((pix2.rgbRed-pix1.rgbRed)>maxr) maxr = pix2.rgbRed;
					}
				}
				pix1.rgbBlue=(BYTE)(255-maxb);
				pix1.rgbGreen=(BYTE)(255-maxg);
				pix1.rgbRed=(BYTE)(255-maxr);
				tmp.SetPixelColor(x,y,pix1);
			}
		}
	}
	Transfer(tmp);
	return true;
}
////////////////////////////////////////////////////////////////////////////////
/**
 * Adds a random offset to each pixel in the image
 * \param radius: maximum pixel displacement
 * \return true if everything is ok
 */
bool CxImage::Jitter(long radius)
{
	if (!pDib) return false;

	long nx,ny;

	CxImage tmp(*this,pSelection!=0,true,true);
	if (!tmp.IsValid()) return false;

	long xmin,xmax,ymin,ymax;
	if (pSelection){
		xmin = info.rSelectionBox.left; xmax = info.rSelectionBox.right;
		ymin = info.rSelectionBox.bottom; ymax = info.rSelectionBox.top;
	} else {
		xmin = ymin = 0;
		xmax = head.biWidth; ymax=head.biHeight;
	}

	for(long y=ymin; y<ymax; y++){
		info.nProgress = (long)(100*y/head.biHeight);
		if (info.nEscape) break;
		for(long x=xmin; x<xmax; x++){
#if CXIMAGE_SUPPORT_SELECTION
			if (SelectionIsInside(x,y))
#endif //CXIMAGE_SUPPORT_SELECTION
			{
				nx=x+(long)((rand()/(float)RAND_MAX - 0.5)*(radius*2));
				ny=y+(long)((rand()/(float)RAND_MAX - 0.5)*(radius*2));
				if (!IsInside(nx,ny)) {
					nx=x;
					ny=y;
				}
				if (head.biClrUsed==0){
					tmp.SetPixelColor(x,y,GetPixelColor(nx,ny));
				} else {
					tmp.SetPixelIndex(x,y,GetPixelIndex(nx,ny));
				}
#if CXIMAGE_SUPPORT_ALPHA
				tmp.AlphaSet(x,y,AlphaGet(nx,ny));
#endif //CXIMAGE_SUPPORT_ALPHA
			}
		}
	}
	Transfer(tmp);
	return true;
}
////////////////////////////////////////////////////////////////////////////////
/** 
 * generates a 1-D convolution matrix to be used for each pass of 
 * a two-pass gaussian blur.  Returns the length of the matrix.
 * \author [nipper]
 */
int CxImage::gen_convolve_matrix (float radius, float **cmatrix_p)
{
	int matrix_length;
	int matrix_midpoint;
	float* cmatrix;
	int i,j;
	float std_dev;
	float sum;
	
	/* we want to generate a matrix that goes out a certain radius
	* from the center, so we have to go out ceil(rad-0.5) pixels,
	* inlcuding the center pixel.  Of course, that's only in one direction,
	* so we have to go the same amount in the other direction, but not count
	* the center pixel again.  So we double the previous result and subtract
	* one.
	* The radius parameter that is passed to this function is used as
	* the standard deviation, and the radius of effect is the
	* standard deviation * 2.  It's a little confusing.
	*/
	radius = (float)fabs(radius) + 1.0f;
	
	std_dev = radius;
	radius = std_dev * 2;
	
	/* go out 'radius' in each direction */
	matrix_length = int (2 * ceil(radius-0.5) + 1);
	if (matrix_length <= 0) matrix_length = 1;
	matrix_midpoint = matrix_length/2 + 1;
	*cmatrix_p = new float[matrix_length];
	cmatrix = *cmatrix_p;
	
	/*  Now we fill the matrix by doing a numeric integration approximation
	* from -2*std_dev to 2*std_dev, sampling 50 points per pixel.
	* We do the bottom half, mirror it to the top half, then compute the
	* center point.  Otherwise asymmetric quantization errors will occur.
	*  The formula to integrate is e^-(x^2/2s^2).
	*/
	
	/* first we do the top (right) half of matrix */