weighted CDF formula always returns 1 - matlab

Question

I am reading this paper for enhancing image quality.
my problem is that when I am calculating weighted CDF, I always get 1 as output.
here is the sequence of formulas:
which gamma is defined like this:
which Cw is the weighted CDF:
which I think my main problem would be here.
but to be more clear I will add the rest of the formulas too.
corresponding Weighted Histogram Distribution function is:
and Alpha=C(i) which:
which h_c(i) is clipped histogram , and M is the total intensity levels ( which I'm not sure what is the M, I assumed since sum of Pi should be 1 so it must be sum of the hc_i )
and this is how it is clipping the histogram :
and the clipping limit is calculated with this formula:
here is my code:
sample_img = imread('my image path');
sample_img = im2double(sample_img);
L = 256 % The magnitude of each and every color channel is confined within the range [0 , L-1]
redChannel = sample_img(:,:,1);
greenChannel = sample_img(:,:,2);
blueChannel = sample_img(:,:,3);
max_blue = max(max(blueChannel));
max_green = max(max(greenChannel));
max_red = max(max(redChannel));
min_blue = min(min(blueChannel));
min_green = min(min(greenChannel));
min_red = min(min(redChannel));
bn = blueChannel - min_blue;
rn = redChannel - min_red;
gn = greenChannel - min_green;
max_bn = max(max(bn));
max_rn = max(max(rn));
max_gn = max(max(gn));
b_stretched = bn/max_bn;
r_stretched = rn/max_rn;
g_stretched = gn/max_gn;
% Recombine separate color channels into an RGB image.
rgb_stretched_Image = cat(3, r_stretched, g_stretched, b_stretched);
% Convert RGB to HSI
hsi_image = rgb2hsi(rgb_stretched_Image);
intensity = hsi_image(:, :, 3);
figure()
[counts , binLocations] = imhist(intensity);
imhist(intensity);
hist = counts;
% the clipping limit is computed based on the mean value of the
Tc = mean(hist);
% histogram clipping
length_hist = length(hist);
clipped_hist = zeros(1,length_hist);
for hist_id = 1:length_hist
if hist(hist_id)<Tc
disp('<Tc')
disp(hist(hist_id));
clipped_hist(hist_id) = hist(hist_id);
continue
end
disp('>Tc')
clipped_hist(hist_id) = Tc;
end
% the corresponding PDF (p(i))
% this is where I just used sum(clipped_hist) instead of M
Pi = clipped_hist / sum(clipped_hist);
%CDF
Ci = sum(Pi(1:L));
Alpha = Ci;
%Weighted Histogram Distribution function
Pmin = min(Pi);
Pmax = max(Pi);
Pwi = Pmax * power((Pi-Pmin)/(Pmax-Pmin),Alpha);
%weighted PDF sum
intensity_max = max(max(intensity*L));
Sum_Pwi = sum(Pwi(1:intensity_max));
% weighted CDF
Cwi = sum(Pwi(1:intensity_max)/Sum_Pwi);
%gamma
gamma = 1 - Cwi;
%Transformed pixel intensity
tpi = round(power(intensity/intensity_max,gamma));
since as I said the CDF output is always 1 , the enhanced image is always a white image. and as I see this formula, it must always have 1 as it's output. Am I missing something here ?
and am I right with the M value ?