Understanding Image Histograms | Photography | Ant Smith

// JPG image data is encoded to a gama of approx 2.2 in the sRGB colourspace.
// All the magic numbers you see here come from the sRGB specification.
// If you use a different colourspace you will need to modify the
// Linear/Gamma functions shown here
function sRGBLinear ($channel) {
    $c = $channel/255.0;
    if ($c<=0.04045) return $c/12.92;
    return (($c+0.055)/(1.055))**2.4;
} // sRGBLinear
function sRGBGamma ($v) {
    if ($v<=0.0031308)
        $v = $v*12.92;
    else
        $v = 1.055 * ($v**(1.0/2.4)) - 0.055;
    return intval(round($v*255));
} // sRGBGamma
function sRGBLuminance ($r,$g,$b) {
    return sRGBGamma ( 
        0.212655*sRGBLinear($r) +
        0.715158*sRGBLinear($g) +
        0.072187*sRGBLinear($b)
    );
} // sRGBLuminance
function serveHisto ($fn) {
    try {
        $levels = 256;
        $attributes = false;
        
        // make sure the filename is well conditioned
        $fn = str_replace('../','',$fn);
        $fn = str_replace('.jpg','',strtolower($fn));
        $fn = '../'.$fn.'.jpg';
        // extract the attributes we need (width, height, image type)
        try {
            if (is_file($fn)) $attributes = getimagesize($fn);
        }
        catch(Exception $e) {
            throw new Exception('histo size exception:'.$fn);
        }
        if ($attributes===false) 
            throw new Exception('histo size error:'.$fn);
        if (count($attributes)<3) 
            throw new Exception ('histo attribute error:'.$fn.' count='.count($attributes));
        
        $w = $attributes[0];
        $h = $attributes[1];
        if ($w===0 || $h===0) 
            throw new Exception ('histo dimension error:'.$fn.' ('.$attributes[0].','.$attributes[1].')');
        if ($attributes[2]!=2) 
            throw new Exception ('histo type error (non-jpg):'.$fn.' type='.$attributes[2]);
        // generate the level values for the zonal grid
        $linearZones = array (0.5,0.25,0.125,0.0625,0.03125,0.015625,0.0078125,0.00390625,0.00195312,0.00097656);
        $gammaZones = array();
        foreach ($linearZones as $lZone) {
            $gZone = sRGBGamma($lZone);
            $gammaZones[$gZone] = $lZone;
        }
        
        // create the luminosity map of the image for analysis
        // generating the luminosity histogram while we're at it
        $lumHist = array_fill(0,$levels,0);
        $lums = array();
        $img = imagecreatefromjpeg($fn);
        if ($img===false) 
            throw new Exception ('histo get JPG error:'.$fn);
        $tLum = 0.0;
        for($x=0;$x<$w;++$x){
            $lums[$x] = '';
            for($y=0;$y<$h;++$y){
                $rgb=imagecolorat($img,$x,$y);
                $r = ($rgb >> 16) & 0xFF;
                $g = ($rgb >> 8) & 0xFF;
                $b = $rgb & 0xFF;
                $lum = sRGBLuminance($r,$g,$b);
                $tLum += $lum;
                $lums[$x] .= chr($lum);
                ++$lumHist[$lum];
            }
        }
        // Now calculate derived values:
        // min level, max level, mean & std.dev.
        for ($minIdx=0; $minIdx<$levels; $minIdx++)
            if ($lumHist[$minIdx]>0) break;
        
        for ($maxIdx=$levels-1; $maxIdx>=0; $maxIdx--)
            if ($lumHist[$maxIdx]>0) break;
        $mean = round($tLum/($w*$h),2);
        
        $variance = 0.0;
        foreach ($lums as $row) {
            $bytes = str_split($row);
            foreach ($bytes as $lum)
                $variance += pow(ord($lum)-$mean,2);
        }
        $sd = sqrt($variance/($w*$h));
        $sd = round($sd,2);
        // Done the heavy lifting so clean up the data
        imagedestroy($img);
        $lums = null;
        
        // Now generate the output histogram image
        // scaling the histogram data to fit the chosen height
        // The width is determined by how many luminosity levels
        // we have generated
        $height=128;
        $avPop = array_sum($lumHist)/count($lumHist);
        $maxPop = max($lumHist);
        $scale = (float) $height / min($avPop*4,$maxPop);
        $scale = (float) $height / $maxPop;
        for ($x=0; $x<$levels; $x++)
            $lumHist[$x] = intval(round($lumHist[$x]*$scale));
        $histoImg=imagecreatetruecolor($levels,$height+50);
        
        $canvCol = imagecolorallocate($histoImg, 16, 16, 16);
        $histCol = imagecolorallocate($histoImg,160,160,160);
        $gridCol = imagecolorallocate($histoImg, 45,203,243);
        $minCol  = imagecolorallocate($histoImg,247, 22, 22);
        $maxCol  = imagecolorallocate($histoImg, 34,245, 73);
        $textCol = imagecolorallocate($histoImg,160,160,160);
        // fill in each pixel either to historgram colour 
        // or to appropriate canvas colour (ie. taking into 
        // account min/max markers and zonal grid lines)
        for($x=0; $x<$levels; $x++){
            for($y=0; $y<$height; $y++){
                $thisCol = $histCol;
                if ($y>$lumHist[$x]) {
                    $thisCol = $canvCol;
                    if ($x===$minIdx) $thisCol = $minCol;
                    if ($x===$maxIdx) $thisCol = $maxCol;
                    if (array_key_exists($x,$gammaZones)) $thisCol = $gridCol;
                }
                imagesetpixel($histoImg,$x,$height-$y-1,$thisCol);
            }
            // and while we're about it draw the graduate
            // under the histogram to add context.
            $col  = imagecolorallocate($histoImg,$x,$x,$x);
            for($y=0; $y<10; $y++){
                imagesetpixel($histoImg,$x,$height+$y+1,$col);
            }
            imagecolordeallocate($histoImg,$col);
        }
        // Now add the panel data we derived earlier
        $twidth = imagefontwidth(5)*strlen($minIdx);
        $toffset = 5;
        imagestring($histoImg,5,$toffset,139,$minIdx,$minCol);
        $twidth = imagefontwidth(5)*strlen($maxIdx);
        $toffset = $levels-$twidth-5;
        imagestring($histoImg,5,$toffset,139,$maxIdx,$maxCol);
        $t = 'mean: '.$mean.' sd:'.$sd;
        $twidth = imagefontwidth(4)*strlen($t);
        $toffset = intval(round(($levels-$twidth)/2.0));            
        imagestring($histoImg,4,$toffset,159,$t,$textCol);
        // all done now so clean-up and send the image
        imagecolordeallocate($histoImg,$textCol);
        imagecolordeallocate($histoImg,$maxCol);
        imagecolordeallocate($histoImg,$minCol);
        imagecolordeallocate($histoImg,$gridCol);
        imagecolordeallocate($histoImg,$histCol);
        imagecolordeallocate($histoImg,$canvCol);
        try {
            imagewebp ($histoImg, NULL,40) ;
        }
        catch (Exception $e) {
            throw new Exception ('render histo error; w:'.$w.' h:'.$h);
        }
        imagedestroy ($histoImg);
    }
    catch (Exception $e) {
        http_response_code (500);
        try {
            header_remove ('Cache-Control');
            header_remove ('Expires');
            header_remove ('Content-Type');
            header_remove ('Content-Disposition');
            header('Content-Type:text/html; charset=UTF-8');
            header('Cache-Control: max-age=0');
        }
        finally {
            $msg = '';
            $msg .= '
';
            $msg .= '
Serve Histo Error:'.$fn.'
';
            $msg .= '
'.$e->getMessage().'
';
            $msg .= '
processing script:'.pathinfo($e->getFile(),PATHINFO_BASENAME).'
';
            $msg .= '
 at line:'.$e->getLine().'
';                
            $msg .= '
';
            $msg .= '';
            echo $msg;
        }
    }
} // serveHisto