Data commit

Task/Bitmap-Histogram/Octave/bitmap-histogram.octave

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+function h = imagehistogram(imago)
+  if ( isgray(imago) )
+    for j = 0:255
+      h(j+1) = numel(imago( imago == j ));
+    endfor
+  else
+    error("histogram on gray img only");
+  endif
+endfunction
+
+% test
+im = jpgread("Lenna100.jpg");
+img = rgb2gray(im);
+h = imagehistogram(img);
+% let's try to show the histogram
+bar(h);
+pause;
+
+% in order to obtain the requested filtering, we
+% can use median directly on the img, and then
+% use that value, this way:
+m = median(reshape(img, 1, numel(img)));
+disp(m);
+ibw = img;
+ibw( img > m ) = 255;
+ibw( img <= m ) = 0;
+jpgwrite("lennamed_.jpg", ibw, 100);
+% which disagree (128) with the m computed with histog_med (130).
+% If we compute it this way:
+% m = sort(reshape(img, 1, numel(img)))(ceil(numel(img)/2));
+% we obtain 130... but builtin median works as expected, since
+% N (number of pixel of Lenna) is even, not odd.
+
+% but let's use our histogram h instead
+function m = histog_med(histog)
+  from = 0; to = 255;
+  left = histog(from + 1); right = histog(to+1);
+  while ( from != to )
+    if ( left < right )
+      from++; left += histog(from+1);
+    else
+      to--; right += histog(to+1);
+    endif
+  endwhile
+  m = from;
+endfunction
+
+m = histog_med(h);
+disp(m);
+ibw( img > m ) = 255;
+ibw( img <= m ) = 0;
+jpgwrite("lennamed.jpg", ibw, 100);