ximadsp.cpp

用Cximage 库显示各种格式图片小程序

	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:
				BlindSetPixelColor(x,y,HSLtoRGB(c));
				break;
			case 2:
				BlindSetPixelColor(x,y,YUVtoRGB(c));
				break;
			case 3:
				BlindSetPixelColor(x,y,YIQtoRGB(c));
				break;
			case 4:
				BlindSetPixelColor(x,y,XYZtoRGB(c));
				break;
			default:
				BlindSetPixelColor(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()){
		strcpy(info.szLastError,tmp.GetLastError());
		return false;
	}

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

	double correction,ix,iy,ixx,ixy,iyy;
	int x,y,xy0,xp1,xm1,yp1,ym1;

	for(x=1; x<w; x++){
		for(y=1; y<h; y++){

			xy0 = ch->BlindGetPixelIndex(x,y);
			xm1 = ch->BlindGetPixelIndex(x-1,y);
			xp1 = ch->BlindGetPixelIndex(x+1,y);
			ym1 = ch->BlindGetPixelIndex(x,y-1);
			yp1 = ch->BlindGetPixelIndex(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->BlindGetPixelIndex(x+1,y+1) + ch->BlindGetPixelIndex(x-1,y-1) -
				 ch->BlindGetPixelIndex(x-1,y+1) - ch->BlindGetPixelIndex(x+1,y-1))/4.0;

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

			tmp.BlindSetPixelIndex(x,y,(BYTE)min(255,max(0,(xy0 + radius * correction + 0.5))));
		}
	}

	for (x=0;x<=w;x++){
		for(y=0; y<=h; y+=h){
			xy0 = ch->BlindGetPixelIndex(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;

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

			tmp.BlindSetPixelIndex(x,y,(BYTE)min(255,max(0,(xy0 + radius * correction + 0.5))));
		}
	}
	for (x=0;x<=w;x+=w){
		for (y=0;y<=h;y++){
			xy0 = ch->BlindGetPixelIndex(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;

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

			tmp.BlindSetPixelIndex(x,y,(BYTE)min(255,max(0,(xy0 + radius * correction + 0.5))));
		}
	}

	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);
	if (!tmp.IsValid()){
		strcpy(info.szLastError,tmp.GetLastError());
		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-ymin)/(ymax-ymin));
		if (info.nEscape) break;
		for(long x=xmin; x<xmax; x++){
#if CXIMAGE_SUPPORT_SELECTION
			if (BlindSelectionIsInside(x,y))
#endif //CXIMAGE_SUPPORT_SELECTION
				{
				pix1 = BlindGetPixelColor(x,y);
				maxr=maxg=maxb=0;
				for(j=-k2, i=0;j<kmax;j++){
					for(k=-k2;k<kmax;k++, i++){
						if (!IsInside(x+j,y+k)) continue;
						pix2 = BlindGetPixelColor(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.BlindSetPixelColor(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);
	if (!tmp.IsValid()){
		strcpy(info.szLastError,tmp.GetLastError());
		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-ymin)/(ymax-ymin));
		if (info.nEscape) break;
		for(long x=xmin; x<xmax; x++){
#if CXIMAGE_SUPPORT_SELECTION
			if (BlindSelectionIsInside(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.BlindSetPixelColor(x,y,BlindGetPixelColor(nx,ny));
				} else {
					tmp.BlindSetPixelIndex(x,y,BlindGetPixelIndex(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.
	* <DP> modified scaling, so that matrix_lenght = 1+2*radius parameter
	*/
	radius = (float)fabs(0.5*radius) + 0.25f;
	
	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 */
	for (i = matrix_length/2 + 1; i < matrix_length; i++)
    {
		float base_x = i - (float)floor((float)(matrix_length/2)) - 0.5f;
		sum = 0;
		for (j = 1; j <= 50; j++)
		{
			if ( base_x+0.02*j <= radius ) 
				sum += (float)exp (-(base_x+0.02*j)*(base_x+0.02*j) / 
				(2*std_dev*std_dev));
		}
		cmatrix[i] = sum/50;
    }
	
	/* mirror the thing to the bottom half */
	for (i=0; i<=matrix_length/2; i++) {
		cmatrix[i] = cmatrix[matrix_length-1-i];
	}
	
	/* find center val -- calculate an odd number of quanta to make it symmetric,
	* even if the center point is weighted slightly higher than others. */
	sum = 0;
	for (j=0; j<=50; j++)
    {
		sum += (float)exp (-(0.5+0.02*j)*(0.5+0.02*j) /
			(2*std_dev*std_dev));
    }
	cmatrix[matrix_length/2] = sum/51;
	
	/* normalize the distribution by scaling the total sum to one */
	sum=0;
	for (i=0; i<matrix_length; i++) sum += cmatrix[i];
	for (i=0; i<matrix_length; i++) cmatrix[i] = cmatrix[i] / sum;
	
	return matrix_length;
}
////////////////////////////////////////////////////////////////////////////////
/**
 * generates a lookup table for every possible product of 0-255 and
 * each value in the convolution matrix.  The returned array is
 * indexed first by matrix position, then by input multiplicand (?)
 * value.
 * \author [nipper]
 */
float* CxImage::gen_lookup_table (float *cmatrix, int cmatrix_length)
{
	float* lookup_table = new float[cmatrix_length * 256];
	float* lookup_table_p = lookup_table;
	float* cmatrix_p      = cmatrix;
	
	for (int i=0; i<cmatrix_length; i++)
    {
		for (int j=0; j<256; j++)
		{
			*(lookup_table_p++) = *cmatrix_p * (float)j;
		}
		cmatrix_p++;
    }
	
	return lookup_table;
}
////////////////////////////////////////////////////////////////////////////////
/**
 * this function is written as if it is blurring a column at a time,
 * even though it can operate on rows, too.  There is no difference
 * in the processing of the lines, at least to the blur_line function.
 * \author [nipper]
 */
void CxImage::blur_line (float *ctable, float *cmatrix, int cmatrix_length, BYTE* cur_col, BYTE* dest_col, int y, long bytes)
{
	float scale;
	float sum;
	int i=0, j=0;
	int row;
	int cmatrix_middle = cmatrix_length/2;
	
	float *cmatrix_p;
	BYTE  *cur_col_p;
	BYTE  *cur_col_p1;
	BYTE  *dest_col_p;
	float *ctable_p;
	
	/* this first block is the same as the non-optimized version --
	* it is only used for very small pictures, so speed isn't a
	* big concern.
	*/
	if (cmatrix_length > y)
    {
		for (row = 0; row < y ; row++)
		{
			scale=0;
			/* find the scale factor */
			for (j = 0; j < y ; j++)
			{
				/* if the index is in bounds, add it to the scale counter */
				if ((j + cmatrix_middle - row >= 0) &&
					(j + cmatrix_middle - row < cmatrix_length))
					scale += cmatrix[j + cmatrix_middle - row];
			}
			for (i = 0; i<bytes; i++)
			{
				sum = 0;
				for (j = 0; j < y;