Colorimetry - Revision history

Patapom at 17:08, 20 November 2016

2016-11-20T17:08:40Z

Patapom at 16:10, 20 November 2016

2016-11-20T16:10:20Z

Patapom at 16:08, 20 November 2016

2016-11-20T16:08:33Z

Patapom at 16:02, 20 November 2016

2016-11-20T16:02:04Z

Patapom at 17:01, 3 January 2012

2012-01-03T17:01:16Z

Patapom at 16:58, 3 January 2012

2012-01-03T16:58:27Z

Patapom at 19:49, 1 January 2012

2012-01-01T19:49:57Z

Patapom at 18:56, 1 January 2012

2012-01-01T18:56:47Z

Patapom at 18:10, 1 January 2012

2012-01-01T18:10:50Z

Patapom at 16:08, 1 January 2012

2012-01-01T16:08:36Z

@@ Line 311: / Line 311: @@
 * Most industries use D65 when daylight viewing conditions are required
 * D50 is used by graphic arts industry => more spectrally balanced across spectrum
@@ Line 337: / Line 335: @@
-If you wish to retrieve an arbitrary white point's chromaticity from its Correlated Color Temperature, you can find the generic code I'm using on this page: [[Illuminant_Computation#Custom Illuminant Computation|Custom Illuminant Computation]].
+Please refer to the [[Illuminant_Computation#D-Illuminant Computation|D Illuminant Computation]] page for an interesting way of computing the SPD from CCT.

@@ Line 336: / Line 336: @@
 The process of calculating the white point discards a great deal of information about the profile of the illuminant, and so although it is true that for every illuminant the exact white point can be calculated, it is not the case that knowing the white point of an image alone tells you a great deal about the illuminant that was used to record it.
-If you wish to retrieve a white point's chromaticity from its Correlated Color Temperature, you can find the code I'm using [[Colorimetry_DIlluminant_Computation|here]].
 ===White points of standard illuminants===

← Older revision		Revision as of 16:08, 20 November 2016
Line 312:		Line 312:
	* D50 is used by graphic arts industry => more spectrally balanced across spectrum		* D50 is used by graphic arts industry => more spectrally balanced across spectrum

−	Please refer to the [[~~Colorimetry_DIlluminant_Computation~~\|D Illuminant Computation]] page for an interesting way of computing the SPD from CCT.	+	Please refer to the [[Illuminant_Computation#D-Illuminant Computation\|D Illuminant Computation]] page for an interesting way of computing the SPD from CCT.

@@ Line 2: / Line 2: @@
 A color space is the 3-dimensional space in which colors can be represented. 3 dimensions are enough for all applications to describe a color faithfully, but various conventions can be chosen to select each dimension depending on the intended goal (processing, display, accuracy, perception, etc.).
-Some of the color spaces are [[Colorimetry#CIE_XYZ|CIE XYZ]], [[Colorimetry#CIE_xyY|CIE xyY]], [[Colorimetry#CIE_LAB|CIE LAB]], [[Colorimetry#RGB|RGB]], HSV, HSB, HSL, YUV.
+Some of the color spaces are [[Colorimetry#CIE_XYZ|CIE XYZ]], [[Colorimetry#CIE_xyY|CIE xyY]], [[Colorimetry#CIE_LAB|CIE LAB]], [[Colorimetry#RGB|RGB]], [[Colorimetry#HSL_and_HSV|HSV, HSL]], HSB, [[Colorimetry#YUV|YUV]].
 These color spaces can be categorized in different ways:
@@ Line 180: / Line 180: @@
 ==Difference between Color Space and Color Profile==
-It's important not to confuse the RGB Color Spaces described earlier with some [[Color_Profile|Color Profiles]] like [[Color_Profile#sRGB|sRGB]] or [[Color_Profile#Adobe_RGB|Adobe RGB]].
+It's important not to confuse the RGB Color Spaces described earlier, with the [[Color_Profile|Color Profiles]] like [[Color_Profile#sRGB|sRGB]] or [[Color_Profile#Adobe_RGB|Adobe RGB]].
-The latter are color profiles that describe how to map a RGB value to the entire [http://en.wikipedia.org/wiki/Gamut gamut] of [[Colorimetry#CIE_xyY|chromaticities]] and how to interpret the luminance (linear or gamma-corrected).
+The color profiles describe how to map a RGB value to the entire [http://en.wikipedia.org/wiki/Gamut gamut] of [[Colorimetry#CIE_xyY|chromaticities]] and how to interpret the luminance (e.g. linear or gamma-corrected).
@@ Line 335: / Line 335: @@
 If an image is recorded in tristimulus coordinates (or in values which can be converted to and from them), then the white point of the illuminant used gives the maximum value of the tristimulus coordinates that will be recorded at any point in the image, in the absence of fluorescence. It is called the white point of the image.
 The process of calculating the white point discards a great deal of information about the profile of the illuminant, and so although it is true that for every illuminant the exact white point can be calculated, it is not the case that knowing the white point of an image alone tells you a great deal about the illuminant that was used to record it.
 ===White points of standard illuminants===
 A list of standardized illuminants, their CIE chromaticity coordinates (x,y) of a perfect reflecting (or transmitting) diffuser, and their correlated color temperatures (CCTs) are given below. The CIE chromaticity coordinates are given for both the 2 degree field of view (1931) and the 10 degree field of view (1964). The color swatches represent the hue of each white point, calculated with luminance Y=0.54 and the standard observer, assuming correct sRGB display calibration.
 {| cellspacing="0" align="center" class="wikitable" style="width:60em"

← Older revision		Revision as of 17:01, 3 January 2012
Line 35:		Line 35:

	Occasionally, there are precise rules for converting between non-absolute color spaces. For example [[Colorimetry#HSL_and_HSV\|HSL and HSV]] spaces are defined as mappings of RGB. Both are non-absolute, but the conversion between them should maintain the same color. However, in general, ''converting between two non-absolute color spaces (for example, RGB to CMYK) or between absolute and non-absolute color spaces (for example, RGB to Lab*) is almost a meaningless concept''.		Occasionally, there are precise rules for converting between non-absolute color spaces. For example [[Colorimetry#HSL_and_HSV\|HSL and HSV]] spaces are defined as mappings of RGB. Both are non-absolute, but the conversion between them should maintain the same color. However, in general, ''converting between two non-absolute color spaces (for example, RGB to CMYK) or between absolute and non-absolute color spaces (for example, RGB to Lab*) is almost a meaningless concept''.
		+
		+
		+	See also the [[Color_Transforms\|Color Transforms]] page for helpful formulas transforming from one color space to another.

← Older revision		Revision as of 16:58, 3 January 2012
Line 115:		Line 115:

	===CIE LAB===		===CIE LAB===
		+	[[File:Lab_Colorsphere.jpg\|thumb\|350px]]
	(Source: http://en.wikipedia.org/wiki/Lab_color_space)		(Source: http://en.wikipedia.org/wiki/Lab_color_space)

← Older revision		Revision as of 19:49, 1 January 2012
Line 182:		Line 182:

	=Rendering Intent=		=Rendering Intent=
		+	(Source: http://en.wikipedia.org/wiki/Color_management#Rendering_intent)

		+	When the gamut of source color space exceeds that of the destination, saturated colors are liable to become clipped (inaccurately represented), or more formally burned. The color management module can deal with this problem in several ways. The ICC specification includes four different rendering intents:
		+	* Absolute colorimetric
		+	* Relative colorimetric
		+	* Perceptual
		+	* Saturation.

		+	==Absolute Colorimetric==
		+	Absolute colorimetry and relative colorimetry actually use the same table but differ in the adjustment for the white point media. If the output device has a much larger gamut than the source profile, i.e., all the colors in the source can be represented in the output, using the absolute colorimetry rendering intent would "ideally" (ignoring noise, precision, etc.) give an exact output of the specified [[Colorimetry#CIE_LAB\|CIELAB]] values. Perceptually, the colors may appear incorrect, but instrument measurements of the resulting output would match the source. Colors outside of the proof print system's possible color are mapped to the boundary of the color gamut. Absolute colorimetry is useful to get an exact specified color (e.g., IBM blue), or to quantify the accuracy of mapping methods.
		+
		+
		+	According to the Photoshop definition:
		+
		+	Attempts to match the absolute Lab coordinates of the destination colors to the absolute Lab coordinates of the source colors. Does not adjust for different media white points. Mostly used for "logo" colors and hard proofing.
		+
		+
		+	==Relative Colorimetric==
		+	The goal in relative colorimetry is to be truthful to the specified color, with only a correction for the media. Relative colorimetry is useful in proofing applications, since you are using it to get an idea of how a print on one device will appear on a different device. Media differences are the only thing you really would like to adjust for. Obviously there has to be some gamut mapping going on also. Usually this is done in a way where hue and lightness are maintained at the cost of reduced saturation. Relative colorimetric is the default rendering intent on most systems.
		+
		+
		+	According to the Photoshop definition:
		+
		+	Attempts to match the media-relative Lab coordinates of the destination colors to the media-relative Lab coordinates of the source colors. The source white point is mapped to the destination white point. Recommended for most conversions, especially when most source colors are already inside the destination gamut.
		+
		+
		+	==Perceptual and Saturation==
		+	The perceptual and saturation intents are where the results really depend upon the profile maker. This is even how some of the competitors in this market differentiate themselves. These intents should be created by the profile maker so that pleasing images occur with the perceptual intent while eye-catching business graphics occur with the saturation intent. This is achieved through the use of different perceptual remaps of the data as well as different gamut mapping methods. Perceptual rendering is recommended for color separation.
		+
		+
		+	In practice, photographers almost always use relative or perceptual intent, as for natural images, absolute causes color cast, while saturation produces unnatural colors. Relative intent handles out-of-gamut by clipping (burning) these colors to the edge of the gamut, leaving in-gamut colors unchanged, while '''perceptual intent smoothly moves out-of-gamut colors into gamut, preserving gradations, but distorts in-gamut colors in the process'''. If an entire image is in-gamut, relative is perfect, but when there are out of gamut colors, which is more preferable depends on a case-by-case basis.
		+
		+	'''Saturation intent is most useful in charts and diagrams''', where there is a discrete palette of colors which one wishes to have saturated (to "pop"), but where the specific hue is less important.
		+
		+
		+	According to the Photoshop definition:
		+
		+	Perceptual: Requests a visually pleasing rendering, preserving the visual relationships between source colors. Often used to render wide gamut source images, where preserving the relationship of colors inside and outside the destination gamut is more important than exactly matching the colors inside the destination gamut.
		+
		+	Saturation: Requests a highly saturated rendering, at the possible expense of color accuracy. Mostly used for business graphics (Pies, Charts, etc.), where color accuracy is less important than having a highly saturated result.

← Older revision		Revision as of 18:56, 1 January 2012
Line 70:		Line 70:

	==Device-Independent Color Spaces==		==Device-Independent Color Spaces==
		+	These color spaces can also be used as [[Color_Profile\|''Profile Connection Space'']] (PCS).
		+
		+	Color Space 1 → PCS (CIELAB or CIEXYZ) → Color space 2; conversions into and out of the PCS are each specified by a [[Color_Profile\|color profile]].
		+

	===CIE XYZ===		===CIE XYZ===

@@ Line 34: / Line 34: @@
 One part of the definition of an absolute color space is the viewing conditions. The same color, viewed under different natural or artificial lighting conditions, will look different. Those involved professionally with color matching may use viewing rooms, lit by standardized lighting.
-Occasionally, there are precise rules for converting between non-absolute color spaces. For example HSL and HSV spaces are defined as mappings of RGB. Both are non-absolute, but the conversion between them should maintain the same color. However, in general, ''converting between two non-absolute color spaces (for example, RGB to CMYK) or between absolute and non-absolute color spaces (for example, RGB to L*a*b*) is almost a meaningless concept''.
+Occasionally, there are precise rules for converting between non-absolute color spaces. For example [[Colorimetry#HSL_and_HSV|HSL and HSV]] spaces are defined as mappings of RGB. Both are non-absolute, but the conversion between them should maintain the same color. However, in general, ''converting between two non-absolute color spaces (for example, RGB to CMYK) or between absolute and non-absolute color spaces (for example, RGB to L*a*b*) is almost a meaningless concept''.
@@ Line 165: / Line 165: @@
 Please refer to the [[Color_Transforms|Color Transforms]] page for useful transformations between color spaces.

@@ Line 156: / Line 156: @@
 ===HSL and HSV===
 (Source: http://en.wikipedia.org/wiki/HSL_and_HSV)
-[[File:Hsl-hsv_models.png|thumb|300px]]
+[[File:Hsl-hsv_models.png|thumb|300px|HSL (a–d) and HSV (e–h). Above (a, e): cut-away 3D models of each. Below: two-dimensional plots showing two of a model’s three parameters at once, holding the other constant: cylindrical shells (b, f) of constant saturation, in this case the outside surface of each cylinder; horizontal cross-sections (c, g) of constant HSL lightness or HSV value, in this case the slices halfway down each cylinder; and rectangular vertical cross-sections (d, h) of constant hue, in this case of hues 0° red and its complement 180° cyan.]]
 HSL and HSV are the two most common cylindrical-coordinate representations of points in an RGB color model, which rearrange the geometry of RGB in an attempt to be more intuitive and perceptually relevant than the cartesian (cube) representation. They were developed in the 1970s for computer graphics applications, and are used for color pickers, in color-modification tools in image editing software, and less commonly for image analysis and computer vision.