rawToRGB_BooleanMatrixSelection.m

function [redPixels, greenPixels, bluePixels] = rawToRGB_BooleanMatrixSelection(cfaPatternDimensions, cfaPatternExif, imgData)

  timeStart = time();

  %%
  %% Returns boolean matrix with values set to one corresponding to pixels in
  %% imgData that correspond to pixels of the specified cfaColor
  %%
  function pixelColorBooleanTable = genPixelColorBooleanTable(cfaColor)

    %% generate boolean table of M x N with values equal to 1 for pixels of color we want
    table = logical(cfaPatternAsMatrix == cfaColor);

    %% scale (repeat) table so its large enough to cover the entire image data. this
    %% requires rounding up the repeat count to an even multiple of the CFA dimensions
    pixelColorBooleanTable  = repmat(table,  floor ((imgHeight+cfaPatternRows-1)/cfaPatternRows),
     floor ((imgWidth+cfaPatternCols-1)/cfaPatternCols));

    %% round size of table down if necessary to exactly fit the size of the image data
    pixelColorBooleanTable = pixelColorBooleanTable(1:imgHeight, 1:imgWidth);
  end

  CFA_RED = 0;
  CFA_GREEN = 1;
  CFA_BLUE = 2;

  imgHeight = size(imgData, 1);
  imgWidth = size(imgData, 2);

  %%
  %% build three boolean matricies, one per color, that will be used to select
  %% values out of the image data corresponding to the CFA location of those
  %% colors
  %%
  cfaPatternRows = cfaPatternDimensions(1);
  cfaPatternCols = cfaPatternDimensions(2);
  cfaPatternAsMatrix = reshape(cfaPatternExif, [cfaPatternRows cfaPatternCols])';
  redBooleanTable = genPixelColorBooleanTable(CFA_RED);
  greenBooleanTable = genPixelColorBooleanTable(CFA_GREEN);
  blueBooleanTable = genPixelColorBooleanTable(CFA_BLUE);

  %% extract pixel data for each of the colors we want
  redPixels   = imgData(redBooleanTable);
  greenPixels = imgData(greenBooleanTable);
  bluePixels  = imgData(blueBooleanTable);

  printf("Execution time: %.4f\n", time() - timeStart);
end