void AtrousGabor::_image_prod(IMAGE_PTR i1, IMAGE_PTR i2, IMAGE_PTR out)
{
#ifdef USE_IPP
IppiSize roiSize = {m_i_colsext, m_i_linesext};
ippiMul_32f_C1R(i1, m_i_strideext, i2, m_i_strideext, out, m_i_strideext, roiSize);
#else
int i, j;
for(i = 0; i < m_i_linesext; i++)
for(j = 0; j < m_i_colsext; j++)
out[i*m_i_stridepix+j] = i1[i*m_i_stridepix+j]*i2[i*m_i_stridepix+j];
#endif
}
Ipp32f (*ParticleStatistics(Image2D &image_localmax, Image2D &image_in,
const int mask_radius, const int feature_radius, int &counter))[8]
{
IppStatus status;
//setup kernels
Convolution_Kernel ConvolutionKernels(mask_radius, image_localmax.get_width(), image_localmax.get_length());
//Convert 32-bit FP image data in image_localmax to 8-bit integer data
Ipp8u *localmaxdata = ippsMalloc_8u((int) image_localmax.get_numberofpixels());
int stepsize = image_localmax.get_width();
IppiSize fullROI = image_localmax.get_ROIfull();
status = ippiConvert_32f8u_C1R(image_localmax.get_image2D(), image_localmax.get_stepsize(),
localmaxdata, stepsize, fullROI, ippRndNear);
//Determine the number of particles (raw; not yet excluded from border region)
Ipp64f numberofmaxima = 0;
status = ippiSum_8u_C1R(localmaxdata, stepsize, image_localmax.get_ROIfull(), &numberofmaxima);
//Set up structures for counting particle data
int numberofpixels = image_localmax.get_numberofpixels();
Ipp32f (*particledata)[8] = new Ipp32f[(int) numberofmaxima + 1][8];
//border region (local maxima here are excluded from future operations)
int border = feature_radius; //minimum distance from the border, in pixels
int minx = border, miny = border;
int maxx = image_localmax.get_width() - minx;
int maxy = image_localmax.get_height() - miny;
int xval = 0;
int yval = 0;
counter = 0; //index that keeps track of which particle
int imagewidth = image_in.get_width();
//determine integer x and y values (in pixels) for each local maximum outside
//of border exclusion area
for(int j = 0; j < numberofpixels; j++) {
if(localmaxdata[j] == 1) {
xval = image_in.getx(j);
yval = image_in.gety(j);
if (xval > minx && xval < maxx && yval > miny && yval < maxy) {
particledata[counter][0] = j;
particledata[counter][1] = xval;
particledata[counter][2] = yval;
counter++;
}
}
}
//extract local region around each maximum
int extract_radius = mask_radius;
int extract_diameter = 2 * extract_radius + 1;
int extract_size = extract_diameter * extract_diameter;
int extract_step = 4 * extract_diameter;
IppiSize extract_ROI = {extract_diameter, extract_diameter};
int extract_offset = extract_radius * (1 + image_in.get_width()); //calculate _relative_ offset (in pixels) of the array index
Ipp32f *extracted_square = ippsMalloc_32f(extract_size);
Ipp32f *multiply_result = ippsMalloc_32f(extract_size);
Ipp32f *inputimage = ippsMalloc_32f(image_in.get_numberofpixels());
status = ippiCopy_32f_C1R(image_in.get_image2D(), image_in.get_stepsize(),
inputimage, image_in.get_stepsize(), image_in.get_ROIfull());
for(int i = 0; i < counter; i++) {
int extract_index = particledata[i][0];
int copy_offset = extract_index - extract_offset; //this is the starting point for ROI (in pixels!!)
status = ippiCopy_32f_C1R(inputimage + copy_offset, image_in.get_stepsize(),
extracted_square, extract_step, extract_ROI);
//Calculate mass
Ipp64f total_mass = 0;
status = ippiMul_32f_C1R(extracted_square, extract_step, ConvolutionKernels.get_circle_kernel(), ConvolutionKernels.get_kernel_step(),
multiply_result, extract_step, extract_ROI);
status = ippiSum_32f_C1R(multiply_result, extract_step, extract_ROI, &total_mass, ippAlgHintNone);
//Calculate x-offset (to be added to integral position)
Ipp64f x_sum = 0;
status = ippiMul_32f_C1R(extracted_square, extract_step, ConvolutionKernels.get_ramp_x_kernel(), ConvolutionKernels.get_kernel_step(),
multiply_result, extract_step, extract_ROI);
status = ippiSum_32f_C1R(multiply_result, extract_step, extract_ROI, &x_sum, ippAlgHintNone);
Ipp32f x_offset = (x_sum / total_mass) - extract_radius - 1;
//Calculate y-offset (to be added to integral position)
Ipp64f y_sum = 0;
status = ippiMul_32f_C1R(extracted_square, extract_step, ConvolutionKernels.get_ramp_y_kernel(), ConvolutionKernels.get_kernel_step(),
multiply_result, extract_step, extract_ROI);
status = ippiSum_32f_C1R(multiply_result, extract_step, extract_ROI, &y_sum, ippAlgHintNone);
Ipp32f y_offset = (y_sum / total_mass) - extract_radius - 1;
//Calculate r^2
Ipp64f r2_sum = 0;
status = ippiMul_32f_C1R(extracted_square, extract_step, ConvolutionKernels.get_r2_kernel(), ConvolutionKernels.get_kernel_step(),
multiply_result, extract_step, extract_ROI);
status = ippiSum_32f_C1R(multiply_result, extract_step, extract_ROI, &r2_sum, ippAlgHintNone);
Ipp32f r2_val = r2_sum / total_mass;
//Calculate "multiplicity": how many particles are within the area calculated by the masks
Ipp64f multiplicity = 0;
status = ippiSum_32f_C1R(image_localmax.get_image2D()+copy_offset, image_localmax.get_stepsize(),
extract_ROI, &multiplicity, ippAlgHintNone);
Ipp32f multiplicity_val = multiplicity;
//assign values to particle data array
if (total_mass > 0) {
particledata[i][1] += x_offset;
particledata[i][2] += y_offset;
particledata[i][3] = x_offset;
particledata[i][4] = y_offset;
particledata[i][5] = total_mass;
particledata[i][6] = r2_val;
particledata[i][7] = multiplicity_val;
}
}
//Cleanup memory (this part is critical---program otherwise crashes!!)
ippsFree(extracted_square);
extracted_square = NULL;
ippsFree(multiply_result);
multiply_result = NULL;
ippsFree(inputimage);
inputimage = NULL;
ippsFree(localmaxdata);
localmaxdata = NULL;
return particledata;
}
