Quantize image using lloyds algorithm

I would like to quantize an image using lloyds algorithm in order to calculate the MSE of an image quantized using the lloyds algorithm. I understand that partition are the levels boundaries and codebook returns the values to be assigned to pixels in each partition range. But i do not understand how to implement the two in order to quantize my image. I've posted my code below, thank you in advance for your time and help!

[M,N] = size(Pic);

training_set = double(Pic(:));

training_set = reshape(training_set,N*M,1);

MSELloyd = zeros(1,7);

for s = 7:-1:1 

      len = 2.^s;

      [partition, codebook] = lloyds(training_set, len);

      [PicLloyd ,index] = imquantize(Pic,partition,codebook); 

      PicLloyd = im2uint8(PicLloyd);

      MSELloyd(s) = immse(PicLloyd,Pic);

end

figure; plot(MSELloyd); title('MSE of image quantized by Lloyds');

[Naushad Varish]

for s = 7:-1:1 
      len = 2.^s;
      [partition, codebook] = lloyds(training_set, len);
      [PicLloyd ,index] = imquantize(Pic,partition,codebook); 
      PicLloyd = im2uint8(PicLloyd);
      MSELloyd(s) = immse(PicLloyd,Pic);
end

You should remove the for loop and these two lines i.e.

PicLloyd = im2uint8(PicLloyd);
    MSELloyd(s) = immse(PicLloyd,Pic); from your code

Answer 1

[Naushad Varish]

Your correct code is

s = 7:-1:0
      len = 2.^s;
      [partition, codebook] = lloyds(training_set, len);
      [PicLloyd ,index] = imquantize(Pic,partition,codebook);

Figure, imshow(PicLloyd), 
max_t=double(max(gray(:)));
% PSNR calculation
squaredErrorImage = (double(gray) - double(PicLloyd)) .^ 2;
mse = sum(sum(squaredErrorImage)) / (M * N);
PSNR = 20 * log10(max_t/ mse)