void AtrousGabor::_image_sub(IMAGE_PTR i1, IMAGE_PTR i2, IMAGE_PTR out)
{
#ifdef USE_IPP
IppiSize roiSize = {m_i_colsext, m_i_linesext};
ippiSub_32f_C1R(i2, m_i_strideext, i1, 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
}
IppStatus BandPass_2D(Image2D &image_in, Image2D &image_bandpassed, const int feature_radius, const int hwhm_length)
{
//set status variable
IppStatus status;
Gaussian_Kernel GaussKernel(feature_radius, hwhm_length, image_in.get_width(), image_in.get_length());
Convolution_Kernel ConvolutionKernels(feature_radius, image_in.get_width(), image_in.get_length());
Tophat_Kernel TopHatKernel(feature_radius, image_in.get_width(), image_in.get_length());
int number_of_pixels = image_in.get_numberofpixels();
int step_size = image_in.get_stepsize();
//Create and initialize intermediate images
Image2D image_gauss_col(image_in.get_length(), image_in.get_width());
Image2D image_gauss_rowcol(image_in.get_length(), image_in.get_width());
Image2D image_tophat(image_in.get_length(), image_in.get_width());
//Gaussian kernel convolution
status = ippiFilterColumn_32f_C1R(image_in.get_image2D() + GaussKernel.get_offset(), step_size,
image_gauss_col.get_image2D() + GaussKernel.get_offset(), step_size,
GaussKernel.get_ROI_size(), GaussKernel.get_gaussian_kernel(),
GaussKernel.get_kernel_length(), GaussKernel.get_anchor_point());
status = ippiFilterRow_32f_C1R(image_gauss_col.get_image2D() + GaussKernel.get_offset(), step_size,
image_gauss_rowcol.get_image2D() + GaussKernel.get_offset(), step_size,
GaussKernel.get_ROI_size(), GaussKernel.get_gaussian_kernel(),
GaussKernel.get_kernel_length(), GaussKernel.get_anchor_point());
/*
//tophat kernel convolution/filterbox operation
status = ippiFilterBox_32f_C1R(image_in.get_image2D() + TopHatKernel.get_offset(), step_size,
image_tophat.get_image2D() + TopHatKernel.get_offset(), step_size,
TopHatKernel.get_ROI_size(), TopHatKernel.get_mask_size(),
TopHatKernel.get_anchor_point());
*/
//change by Eli Sloutskin: take away bias of square filtering kernel
status = ippiConvValid_32f_C1R(image_in.get_image2D(), step_size, image_in.get_ROIfull(),
ConvolutionKernels.get_circle_kernel(), ConvolutionKernels.get_kernel_step(), ConvolutionKernels.get_kernel_size(),
image_tophat.get_image2D() + ConvolutionKernels.get_offset(), step_size);
ippiDivC_32f_C1IR(3*feature_radius*feature_radius, image_tophat.get_image2D(),image_tophat.get_stepsize(),image_tophat.get_ROIfull());
//subtract the two images
status = ippiSub_32f_C1R(image_tophat.get_image2D() + TopHatKernel.get_offset(), step_size,
image_gauss_rowcol.get_image2D()+TopHatKernel.get_offset(), step_size,
image_bandpassed.get_image2D() + TopHatKernel.get_offset(), step_size,
TopHatKernel.get_ROI_size());
//cutoff values below zero
status = ippiThreshold_LTVal_32f_C1IR(image_bandpassed.get_image2D() + TopHatKernel.get_offset(), step_size,
TopHatKernel.get_ROI_size(),0,0);
return status;
}
IppStatus FindLocalMax_2D(Image2D &image_bpass, Image2D &image_bpass_thresh, Image2D &image_subtracted,
const int intensity_threshold, const int dilation_radius)
{
IppStatus status;
Image2D image_dilated(image_bpass.get_length(), image_bpass.get_width());
Dilation_Kernel DilationKernel(dilation_radius, image_bpass.get_width(), image_bpass.get_length());
//Threshold darker pixels in bandpassed image (in preparation for later subtraction)
RecenterImage(image_bpass);
status = ippiThreshold_LTVal_32f_C1R(image_bpass.get_image2D(), image_bpass.get_stepsize(),
image_bpass_thresh.get_image2D(), image_bpass_thresh.get_stepsize(),
image_bpass.get_ROIfull(), intensity_threshold, intensity_threshold);
//Dilate Bandpassed image with a circular kernel
status = ippiSet_32f_C1R(intensity_threshold, image_dilated.get_image2D(), image_dilated.get_stepsize(),
image_dilated.get_ROIfull());
status = ippiDilate_32f_C1R(
//image_bpass.get_image2D() + DilationKernel.get_offset(), image_bpass.get_stepsize(),
image_bpass_thresh.get_image2D() + DilationKernel.get_offset(), image_bpass_thresh.get_stepsize(),
image_dilated.get_image2D()+ DilationKernel.get_offset(), image_dilated.get_stepsize(),
DilationKernel.get_ROI_size(), DilationKernel.get_dilation_kernel(), DilationKernel.get_mask_size(),
DilationKernel.get_anchor_point());
//subtract, such that resulting array is negative to zero (for later exponentation)
status = ippiSub_32f_C1R(
image_dilated.get_image2D(), image_dilated.get_stepsize(),
image_bpass.get_image2D(), image_bpass.get_stepsize(),
image_subtracted.get_image2D(), image_subtracted.get_stepsize(),
image_bpass.get_ROIfull());
//exponentiate subtracted array, then threshold
status = ippiExp_32f_C1IR(image_subtracted.get_image2D(), image_subtracted.get_stepsize(),
image_subtracted.get_ROIfull());
status = ippiThreshold_LTValGTVal_32f_C1IR(image_subtracted.get_image2D(), image_subtracted.get_stepsize(),
image_subtracted.get_ROIfull(), 1-epsilon, 0, 1-epsilon, 1);
return status;
}
