Improved DNG workflow

mdouchement · Jan 1, 2019 · 9f12456 · 9f12456
1 parent 994de0d
commit 9f12456
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Showing 2 changed files with 50 additions and 48 deletions.
diff --git a/const.go b/const.go
@@ -17,7 +17,7 @@ const (
 
 	ifdLen = 12 // Length of an IFD entry in bytes.
 
-	// TIFF variants
+	// TIFF variantes
 	fTIFF = 0
 	fDNG  = 1
 )

diff --git a/reader.go b/reader.go
@@ -26,7 +26,6 @@ import (
 	"github.com/mdouchement/hdr/format"
 	"github.com/mdouchement/hdr/hdrcolor"
 	"github.com/mdouchement/tiff/bayer"
-	"gonum.org/v1/gonum/mat"
 )
 
 // decode decodes the raw data of an image.
@@ -91,7 +90,7 @@ func (d *decoder) decode(dst image.Image, xmin, ymin, xmax, ymax int) error {
 		}
 		// Step 1 - Linearizing + Luminance ReScale used in Bayer.
 		if t, exists := d.features[tLinearizationTable]; exists {
-			fmt.Println("You need to linearize the CFA:", t.val)
+			fmt.Println("You may need to linearize the CFA:", t.val)
 		}
 		if t, exists := d.features[tBlackLevel]; exists {
 			opts.BlackLevel = t.asFloat(0)
@@ -103,56 +102,59 @@ func (d *decoder) decode(dst image.Image, xmin, ymin, xmax, ymax int) error {
 		}
 
 		// Step 2 - White Balancing
-		// if t, exists := d.features[tAsShotNeutral]; exists {
-		// 	// Invert the values and then rescale them all so that the green multiplier is 1.
-		// 	opts.WhiteBalance = make([]float64, len(t.val))
-		// 	for i := range t.val {
-		// 		opts.WhiteBalance[i] = 1 / t.asFloat(i)
-		// 	}
-		// 	opts.WhiteBalance[0] /= opts.WhiteBalance[1]
-		// 	opts.WhiteBalance[1] /= opts.WhiteBalance[1]
-		// 	opts.WhiteBalance[2] /= opts.WhiteBalance[1]
-		// } else {
-		// 	opts.WhiteBalance = []float64{1, 1, 1}
-		// }
-		opts.WhiteBalance = []float64{1, 1, 1}
-
-		// Step 3 - Demosaicing
-		bayer := bayer.NewBilinear(d.buf, opts)
-
-		// Step 4 - Color Space Correction  TODO
-		camToXYZ := []float64{}
-		if t, exists := d.features[tColorMatrix2]; exists {
-			data := make([]float64, len(t.val))
+		if t, exists := d.features[tAsShotNeutral]; exists {
+			// Invert the values and then rescale them all so that the green multiplier is 1.
+			opts.WhiteBalance = make([]float64, len(t.val))
 			for i := range t.val {
-				data[i] = t.asFloat(i)
+				opts.WhiteBalance[i] = 1 / t.asFloat(i)
 			}
-			xyzToCam := mat.NewDense(3, 3, data) // nbOfRows should be equal to len(d.features[tCFAPlaneColor].val)
-			var im mat.Dense
-			im.Inverse(xyzToCam)
-			camToXYZ = append(camToXYZ, im.RawRowView(0)...)
-			camToXYZ = append(camToXYZ, im.RawRowView(1)...)
-			camToXYZ = append(camToXYZ, im.RawRowView(2)...)
-		} else if t, exists := d.features[tColorMatrix1]; exists {
-			data := make([]float64, len(t.val))
-			for i := range t.val {
-				data[i] = t.asFloat(i)
-			}
-			xyzToCam := mat.NewDense(3, 3, data) // nbOfRows should be equal to len(d.features[tCFAPlaneColor].val)
-			var im mat.Dense
-			im.Inverse(xyzToCam)
-			camToXYZ = append(camToXYZ, im.RawRowView(0)...)
-			camToXYZ = append(camToXYZ, im.RawRowView(1)...)
-			camToXYZ = append(camToXYZ, im.RawRowView(2)...)
+			opts.WhiteBalance[0] /= opts.WhiteBalance[1]
+			opts.WhiteBalance[1] /= opts.WhiteBalance[1]
+			opts.WhiteBalance[2] /= opts.WhiteBalance[1]
 		} else {
-			// sRBG->XYZ (D65)
-			camToXYZ = []float64{
-				0.4124564, 0.3575761, 0.1804375,
-				0.2126729, 0.7151522, 0.0721750,
-				0.0193339, 0.1191920, 0.9503041,
-			}
+			opts.WhiteBalance = []float64{1, 1, 1}
 		}
 
+		// Step 3 - Demosaicing
+		bayer := bayer.NewBilinear(d.buf, opts)
+
+		// Step 4 - Color Space Correction
+		// camToXYZ := []float64{}
+		// if t, exists := d.features[tColorMatrix2]; exists {
+		// 	data := make([]float64, len(t.val))
+		// 	for i := range t.val {
+		// 		data[i] = t.asFloat(i)
+		// 	}
+		// 	xyzToCam := mat.NewDense(3, 3, data) // nbOfRows should be equal to len(d.features[tCFAPlaneColor].val)
+		// 	var im mat.Dense
+		// 	im.Inverse(xyzToCam)
+		// 	camToXYZ = append(camToXYZ, im.RawRowView(0)...)
+		// 	camToXYZ = append(camToXYZ, im.RawRowView(1)...)
+		// 	camToXYZ = append(camToXYZ, im.RawRowView(2)...)
+		// } else if t, exists := d.features[tColorMatrix1]; exists {
+		// 	data := make([]float64, len(t.val))
+		// 	for i := range t.val {
+		// 		data[i] = t.asFloat(i)
+		// 	}
+		// 	xyzToCam := mat.NewDense(3, 3, data) // nbOfRows should be equal to len(d.features[tCFAPlaneColor].val)
+		// 	var im mat.Dense
+		// 	im.Inverse(xyzToCam)
+		// 	camToXYZ = append(camToXYZ, im.RawRowView(0)...)
+		// 	camToXYZ = append(camToXYZ, im.RawRowView(1)...)
+		// 	camToXYZ = append(camToXYZ, im.RawRowView(2)...)
+		// } else {
+		// 	// sRBG->XYZ (D65)
+		// 	camToXYZ = []float64{
+		// 		0.4124564, 0.3575761, 0.1804375,
+		// 		0.2126729, 0.7151522, 0.0721750,
+		// 		0.0193339, 0.1191920, 0.9503041,
+		// 	}
+		// }
+		camToXYZ := []float64{
+			0.4124564, 0.3575761, 0.1804375,
+			0.2126729, 0.7151522, 0.0721750,
+			0.0193339, 0.1191920, 0.9503041,
+		}
 		// Step 5 - Brightness & Gamma correction TODO (or not because TMO handle it well)
 
 		//