How to use a naive bayes classifier with this data?

i would like to use a naive bayes classifier to reconstruct an image based on the probabilities calculated within the code below. from what I've gathered i need to fit the probabilities to training data? i just am not sure how to do this. if anyone could point me in the right direction i would greatly appreciate it.

RGB=imread(input('image name\n'));
[indexed,map]= rgb2ind(RGB,8);
imwrite(indexed,map,input('What would you like to save the new image as?\n'));
[numrows, numcolumns]=size(indexed);
dims=numrows*numcolumns;
probability=imhist(indexed,map)./dims

row=1;
column=1;
row_prob=[];
col_prob=[];
row_value=[];
col_value=[];
counter=0;
final_prob_row=[];
final_prob_col=[];
while column<=numcolumns && row<=numrows && counter<=7
    col_prob=sum(indexed(:,column)==counter);
    row_prob=sum(indexed(row,:)==counter);
    col_value=[col_value col_prob];
    row_value=[row_value row_prob];

      if column == numcolumns
          final_prob_row = [final_prob_row;row_value];
          final_prob_col = [final_prob_col;col_value];
          column=0;
          row=0;
          counter=counter+1;
          col_value=[];
          row_value=[];
      end
      column=column+1;
      row=row+1;
  end
  final_final_prob_row=final_prob_row./numrows
  final_final_prob_col=final_prob_col./numcolumns

if i have been to vague or left something out feel free to tell me