--- a
+++ b/libraries/lib_1Shot-MaxPol/utilities/OneShotMaxPol.m
@@ -0,0 +1,34 @@
+function [deblurred_image] = OneShotMaxPol(image_scan_original, deblurring_kernel, model_type, alpha_estimate, c1_estimate, h_psf, significany)
+
+[N_1, N_2, N_3] = size(image_scan_original);
+l = (numel(h_psf(:,1))-1)/2;
+x_polynomial = [-l:l];
+fitting_function = @(amp, alpha, beta, x) generalized_Gaussian_for_fitting(x, amp, alpha, beta);
+for channel = 1: N_3
+    switch model_type
+        case 'Gaussian'
+            beta = 1.8;
+            sigm = alpha_estimate(channel)*0.85;
+        case 'Laplacian'
+            beta = 0.9;
+            sigm = alpha_estimate(channel)*0.5;
+    end
+    %  generate GG smooting filter
+    h_GGaussian = fitting_function(1, sigm, beta, x_polynomial);
+    h_GGaussian = h_GGaussian/sum(h_GGaussian);
+    
+    % generate inverse deconvolution filter
+    inverse_deblurring_kernel = conv(deblurring_kernel(:, channel), h_GGaussian(:), 'same');
+    
+    %  apply inverse deblurring kernel on image observation
+    deblurring_edges_1 = imfilter(image_scan_original(:,:,channel), inverse_deblurring_kernel, 'symmetric', 'conv');
+    deblurring_edges_2 = imfilter(image_scan_original(:,:,channel), inverse_deblurring_kernel', 'symmetric', 'conv');
+    deblurring_edges_12 = imfilter(deblurring_edges_1, inverse_deblurring_kernel', 'symmetric', 'conv');
+    deblurring_edges = deblurring_edges_1 + deblurring_edges_2 + deblurring_edges_12;
+    
+    %
+    gamma_significance(channel) = entropy(image_scan_original(:,:,channel))/(entropy(deblurring_edges)+0.5)*significany;
+    deblurred_image(:,:,channel) = image_scan_original(:,:,channel) + gamma_significance(channel) * deblurring_edges;
+end
+%  convert double format into uint8 format
+deblurred_image = im2uint8(deblurred_image);
\ No newline at end of file