X-Git-Url: https://git.sesse.net/?p=movit;a=blobdiff_plain;f=white_balance_effect.cpp;h=d2e380aaea9c7a8810b7d291ef5e70a695bb4276;hp=8a495fb6f3616b45fb8c78b9988d028b1c8cfa1e;hb=45c9a794d20296b46c5200fde481af9bf9e810f9;hpb=181fca60b28290c92207cfb40e27113e4f5f021c

diff --git a/white_balance_effect.cpp b/white_balance_effect.cpp
index 8a495fb..d2e380a 100644
--- a/white_balance_effect.cpp
+++ b/white_balance_effect.cpp
@@ -39,7 +39,7 @@ Vector3d convert_color_temperature_to_xyz(float T)
 }
 
 // Assuming sRGB primaries, from Wikipedia.
-double rgb_to_xyz_matrix[9] = {
+const double rgb_to_xyz_matrix[9] = {
 	0.4124, 0.2126, 0.0193, 
 	0.3576, 0.7152, 0.1192,
 	0.1805, 0.0722, 0.9505,
@@ -53,9 +53,9 @@ double rgb_to_xyz_matrix[9] = {
  * (Hunt-Pointer-Estevez, or HPE) for the actual perception post-adaptation. 
  *
  * CIECAM02 chromatic adaptation, while related to the transformation we want,
- * is a more complex phenomenon that depends on factors like the total luminance
- * (in cd/m²) of the illuminant, and can no longer be implemented by just scaling
- * each component in LMS space linearly. The simpler way out is to use the HPE matrix,
+ * is a more complex phenomenon that depends on factors like the viewing conditions
+ * (e.g. amount of surrounding light), and can no longer be implemented by just scaling
+ * each component in LMS space. The simpler way out is to use the HPE matrix,
  * which is intended to be close to the actual cone response; this results in
  * the “von Kries transformation” when we couple it with normalization in LMS space.
  *