Add normalize() for simple histogram stretching

Available as normalize() or normalise(). Normalization takes place in LAB place and thus should not change any colors. Existing alpha channels are preserved untouched by normalization.
lovell · Apr 18, 2015 · dce36e0 · dce36e0
1 parent ba034a8
commit dce36e0
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Showing 9 changed files with 240 additions and 3 deletions.
diff --git a/README.md b/README.md
@@ -486,6 +486,10 @@ This is a linear operation. If the input image is in a non-linear colour space s
 
 The output image will still be web-friendly sRGB and contain three (identical) channels.
 
+#### normalize() / normalise()
+
+Stretch histogram to cover full dynamic range before output to enhance contrast.
+
 ### Output options
 
 #### jpeg()

diff --git a/index.js b/index.js
@@ -59,6 +59,7 @@ var Sharp = function(input) {
     sharpenJagged: 2,
     gamma: 0,
     greyscale: false,
+    normalize: 0,
     // output options
     output: '__input',
     progressive: false,
@@ -333,6 +334,15 @@ Sharp.prototype.gamma = function(gamma) {
   return this;
 };
 
+/*
+  Normalize histogram
+*/
+Sharp.prototype.normalize = function(normalize) {
+  this.options.normalize = (typeof normalize === 'boolean') ? normalize : true;
+  return this;
+};
+Sharp.prototype.normalise = Sharp.prototype.normalize;
+
 /*
   Convert to greyscale
 */

diff --git a/package.json b/package.json
@@ -15,7 +15,8 @@
     "Maurus Cuelenaere <mcuelenaere@gmail.com>",
     "Linus Unnebäck <linus@folkdatorn.se>",
     "Victor Mateevitsi <mvictoras@gmail.com>",
-    "Alaric Holloway <alaric.holloway@gmail.com>"
+    "Alaric Holloway <alaric.holloway@gmail.com>",
+    "Bernhard K. Weisshuhn <bkw@codingforce.com>"
   ],
   "description": "High performance Node.js module to resize JPEG, PNG, WebP and TIFF images using the libvips library",
   "scripts": {

diff --git a/src/resize.cc b/src/resize.cc
@@ -83,6 +83,7 @@ struct ResizeBaton {
   double sharpenJagged;
   double gamma;
   bool greyscale;
+  bool normalize;
   int angle;
   bool rotateBeforePreExtract;
   bool flip;
@@ -115,6 +116,7 @@ struct ResizeBaton {
     sharpenJagged(2.0),
     gamma(0.0),
     greyscale(false),
+    normalize(false),
     angle(0),
     flip(false),
     flop(false),
@@ -694,6 +696,86 @@ class ResizeWorker : public NanAsyncWorker {
       image = gammaDecoded;
     }
 
+    // Apply normalization
+    if (baton->normalize) {
+      VipsInterpretation typeBeforeNormalize = image->Type;
+      if (typeBeforeNormalize == VIPS_INTERPRETATION_RGB) {
+        typeBeforeNormalize = VIPS_INTERPRETATION_sRGB;
+      }
+
+      // normalize the luminance band in LAB space:
+      VipsImage *lab;
+      if (vips_colourspace(image, &lab, VIPS_INTERPRETATION_LAB, NULL)) {
+        return Error();
+      }
+      vips_object_local(hook, lab);
+
+      VipsImage *luminance;
+      if (vips_extract_band(lab, &luminance, 0, "n", 1, NULL)) {
+        return Error();
+      }
+      vips_object_local(hook, luminance);
+
+      VipsImage *chroma;
+      if (vips_extract_band(lab, &chroma, 1, "n", 2, NULL)) {
+        return Error();
+      }
+      vips_object_local(hook, chroma);
+
+      VipsImage *stats;
+      if (vips_stats(luminance, &stats, NULL)) {
+        return Error();
+      }
+      vips_object_local(hook, stats);
+      double min = *VIPS_MATRIX(stats, 0, 0);
+      double max = *VIPS_MATRIX(stats, 1, 0);
+
+      VipsImage *normalized;
+      if (min == max) {
+        // Range of zero: create black image
+        if (vips_black(&normalized, image->Xsize, image->Ysize, "bands", 1, NULL )) {
+          return Error();
+        }
+        vips_object_local(hook, normalized);
+      } else {
+        double f = 100.0 / (max - min);
+        double a = -(min * f);
+
+        VipsImage *luminance100;
+        if (vips_linear1(luminance, &luminance100, f, a, NULL)) {
+          return Error();
+        }
+        vips_object_local(hook, luminance100);
+
+        VipsImage *normalizedLab;
+        if (vips_bandjoin2(luminance100, chroma, &normalizedLab, NULL)) {
+          return Error();
+        }
+        vips_object_local(hook, normalizedLab);
+        if (vips_colourspace(normalizedLab, &normalized, typeBeforeNormalize, NULL)) {
+          return Error();
+        }
+        vips_object_local(hook, normalized);
+      }
+
+      if (HasAlpha(image)) {
+        VipsImage *alpha;
+        if (vips_extract_band(image, &alpha, image->Bands - 1, "n", 1, NULL)) {
+          return Error();
+        }
+        vips_object_local(hook, alpha);
+
+        VipsImage *normalizedAlpha;
+        if (vips_bandjoin2(normalized, alpha, &normalizedAlpha, NULL)) {
+          return Error();
+        }
+        vips_object_local(hook, normalizedAlpha);
+        image = normalizedAlpha;
+      } else {
+        image = normalized;
+      }
+    }
+
     // Convert image to sRGB, if not already
     if (image->Type != VIPS_INTERPRETATION_sRGB) {
       // Switch intrepretation to sRGB
@@ -762,10 +844,10 @@ class ResizeWorker : public NanAsyncWorker {
 #if (VIPS_MAJOR_VERSION >= 8 || (VIPS_MAJOR_VERSION >= 7 && VIPS_MINOR_VERSION >= 42))
     } else if (baton->output == "__raw") {
       // Write raw, uncompressed image data to buffer
-      if (baton->greyscale) {
+      if (baton->greyscale || image->Type == VIPS_INTERPRETATION_B_W) {
         // Extract first band for greyscale image
         VipsImage *grey;
-        if (vips_extract_band(image, &grey, 1, NULL)) {
+        if (vips_extract_band(image, &grey, 0, NULL)) {
           return Error();
         }
         vips_object_local(hook, grey);
@@ -1082,6 +1164,7 @@ NAN_METHOD(resize) {
   baton->sharpenJagged = options->Get(NanNew<String>("sharpenJagged"))->NumberValue();
   baton->gamma = options->Get(NanNew<String>("gamma"))->NumberValue();
   baton->greyscale = options->Get(NanNew<String>("greyscale"))->BooleanValue();
+  baton->normalize = options->Get(NanNew<String>("normalize"))->BooleanValue();
   baton->angle = options->Get(NanNew<String>("angle"))->Int32Value();
   baton->rotateBeforePreExtract = options->Get(NanNew<String>("rotateBeforePreExtract"))->BooleanValue();
   baton->flip = options->Get(NanNew<String>("flip"))->BooleanValue();

diff --git a/test/fixtures/2x2_fdcce6.png b/test/fixtures/2x2_fdcce6.png
diff --git a/test/fixtures/grey-8bit-alpha.png b/test/fixtures/grey-8bit-alpha.png
diff --git a/test/fixtures/index.js b/test/fixtures/index.js
@@ -15,9 +15,12 @@ module.exports = {
   inputJpgWithCmykProfile: getPath('Channel_digital_image_CMYK_color.jpg'), // http://en.wikipedia.org/wiki/File:Channel_digital_image_CMYK_color.jpg
   inputJpgWithCmykNoProfile: getPath('Channel_digital_image_CMYK_color_no_profile.jpg'),
   inputJpgWithCorruptHeader: getPath('corrupt-header.jpg'),
+  inputJpgWithLowContrast: getPath('low-contrast.jpg'), // http://www.flickr.com/photos/grizdave/2569067123/
 
   inputPng: getPath('50020484-00001.png'), // http://c.searspartsdirect.com/lis_png/PLDM/50020484-00001.png
   inputPngWithTransparency: getPath('blackbug.png'), // public domain
+  inputPngWithGreyAlpha: getPath('grey-8bit-alpha.png'),
+  inputPngWithOneColor: getPath('2x2_fdcce6.png'),
 
   inputWebP: getPath('4.webp'), // http://www.gstatic.com/webp/gallery/4.webp
   inputTiff: getPath('G31D.TIF'), // http://www.fileformat.info/format/tiff/sample/e6c9a6e5253348f4aef6d17b534360ab/index.htm

diff --git a/test/fixtures/low-contrast.jpg b/test/fixtures/low-contrast.jpg
diff --git a/test/unit/normalize.js b/test/unit/normalize.js
@@ -0,0 +1,136 @@
+'use strict';
+
+var assert = require('assert');
+
+var sharp = require('../../index');
+var fixtures = require('../fixtures');
+
+sharp.cache(0);
+
+describe('Normalization', function () {
+
+  it('uses the same prototype for both spellings', function () {
+    assert.strictEqual(sharp.prototype.normalize, sharp.prototype.normalise);
+  });
+
+  it('spreads rgb image values between 0 and 255', function(done) {
+    sharp(fixtures.inputJpgWithLowContrast)
+      .normalize()
+      .raw()
+      .toBuffer(function (err, data, info) {
+        if (err) throw err;
+        var min = 255, max = 0, i;
+        for (i = 0; i < data.length; i += 3) {
+          min = Math.min(min, data[i], data[i + 1], data[i + 2]);
+          max = Math.max(max, data[i], data[i + 1], data[i + 2]);
+        }
+        assert.strictEqual(0, min);
+        assert.strictEqual(255, max);
+        return done();
+      });
+  });
+
+  it('spreads grayscaled image values between 0 and 255', function(done) {
+    sharp(fixtures.inputJpgWithLowContrast)
+      .gamma()
+      .greyscale()
+      .normalize()
+      .raw()
+      .toBuffer(function (err, data, info) {
+        if (err) throw err;
+        var min = 255, max = 0, i;
+        for (i = 0; i < data.length; i++) {
+          min = Math.min(min, data[i]);
+          max = Math.max(max, data[i]);
+        }
+        assert.strictEqual(0, min);
+        assert.strictEqual(255, max);
+        return done();
+      });
+  });
+
+  it('stretches greyscale images with alpha channel', function (done) {
+    sharp(fixtures.inputPngWithGreyAlpha)
+      .normalize()
+      .raw()
+      .toBuffer(function (err, data, info) {
+        // raw toBuffer does not return the alpha channel (yet?)
+        var min = 255, max = 0, i;
+        for (i = 0; i < data.length; i++) {
+          min = Math.min(min, data[i]);
+          max = Math.max(max, data[i]);
+        }
+        assert.strictEqual(0, min);
+        assert.strictEqual(255, max);
+        return done();
+      });
+  });
+
+  it('keeps an existing alpha channel', function (done) {
+    sharp(fixtures.inputPngWithTransparency)
+      .normalize()
+      .toBuffer(function (err, data, info) {
+        sharp(data)
+          .metadata()
+          .then(function (metadata) {
+            assert.strictEqual(4, metadata.channels);
+            assert.strictEqual(true, metadata.hasAlpha);
+            assert.strictEqual('srgb', metadata.space);
+          })
+          .finally(done);
+      });
+  });
+
+  it('keeps the alpha channel of greyscale images intact', function (done) {
+    sharp(fixtures.inputPngWithGreyAlpha)
+      .normalize()
+      .toBuffer(function (err, data, info) {
+        sharp(data)
+          .metadata()
+          .then(function (metadata) {
+            assert.strictEqual(true, metadata.hasAlpha);
+            // because of complications with greyscale
+            // we return everything in srgb for now.
+            //
+            // assert.strictEqual(2, metadata.channels);
+            // assert.strictEqual('b-w', metadata.space);
+            assert.strictEqual(4, metadata.channels);
+            assert.strictEqual('srgb', metadata.space);
+          })
+          .finally(done);
+      });
+  });
+
+  it('returns a black image for images with only one color', function (done) {
+    sharp(fixtures.inputPngWithOneColor)
+      .normalize()
+      .toBuffer()
+      .bind({})
+      .then(function (imageData) {
+        this.imageData = imageData;
+        return sharp(imageData)
+          .metadata();
+      })
+      .then(function (metadata) {
+        assert.strictEqual(false, metadata.hasAlpha);
+        // because of complications with greyscale
+        // we return everything in srgb for now.
+        //
+        // assert.strictEqual(1, metadata.channels);
+        // assert.strictEqual('b-w', metadata.space);
+        assert.strictEqual(3, metadata.channels);
+        assert.strictEqual('srgb', metadata.space);
+      })
+      .then(function () {
+        return sharp(this.imageData)
+          .raw()
+          .toBuffer();
+      })
+      .then(function (rawData) {
+        // var blackBuffer = new Buffer([0,0,0,0]);
+        var blackBuffer = new Buffer([0,0,0, 0,0,0, 0,0,0, 0,0,0]);
+        assert.strictEqual(blackBuffer.toString(), rawData.toString());
+      })
+      .finally(done);
+  });
+});