Thanks for your reply regarding how to use makeresampler function. I’ve written the codes below to supply the makeresampler with a Hann windowed truncated sinc function interpolating kernel (positive half). I used the function trapz to calculate the are under the function’s curve. Is this the right or proper way to make a normalized interpolating kernel? Thank you for your help.

fc = 0.4;
halfWidth = 3;
samplingRate = 0.001;
x = -halfWidth:samplingRate:halfWidth; % sampling frequency = 1000Hz
hannWind = hann(length(x));
hannWindSinc = hannWind.*(sin(2*pi*fc*x)./(pi*x))';
hannWindSinc(floor(length(x)/2+1),1) = max(hannWindSinc(:));
normHannWindSinc = hannWindSinc/(trapz(hannWindSinc)*samplingRate);
R = makeresampler({halfWidth, normHannWindSinc(floor(length(normHannWindSinc)/2+1):end)'},
 'bound');

Thanks for your guidance. I wonder if I need to supply the R = makeresampler({half_width, positive_half}, padmethod)
with the positive_half of a ‘normalized’ sinc function or it does the normalization inherently when image is resampled during imtransform?

Thank you.

R = makeresampler(interpolant, padmethod)

where interpolant is a two-element cell array of the
form:

{half_width, positive_half}

half_width is a positive scalar designating the half width of a symmetric interpolating kernel. positive_half is a vector of values regularly sampling the kernel on the closed interval [0 positive_half]. So you could just provide a closely-spaced table of samples of the sinc function. You can’t truly interpolate using the sinc function, of course, since it is infinitely wide. You’ll have to choose a suitable width.

I would like to use sinc interpolation in imtransform. I read the Matlab user guide that makeresampler can be used to customize an interpolant for use in imtransform. However, I don’t quite understand how to use makeresampler to creat a sinc interpolant based on the example given there. Can you please guide/show me how to do this?

Thank you very much and your help is truly appreciated!

I think I see the problem. Your script assumes a cubic array, whereas I have a stack of images obtained from microscopy where the interpixelar distance in the plane of an image does not correspond to the image separation distance. Am I correct about this? Is there anyways you can make this script fully functional, like the interpn command (so it would take the same number of inputs and wouldn’t be limited to evenly spaced arrays of data)?

~Roman

I am trying to convert this:

Original_Image_3D_Matrix_INTERPOLATED_all_channels(:,:,:,tiff_channel_number) = …
uint8(interp3(X_original,Y_original,Z_original,…
double(Original_Image_3D_Matrix(:,:,:,tiff_channel_number)),…
X_interpolated,Y_interpolated,Z_interpolated));

to this:

Original_Image_3D_Matrix_INTERPOLATED_all_channels(:,:,:,tiff_channel_number) = …
iminterpn(Original_Image_3D_Matrix(:,:,:,tiff_channel_number),…
X_interpolated,Y_interpolated,Z_interpolated);

the former works while the latter gives me mostly black images. is there anything that jumps out at you that i am doing wrong?