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C

o

l

o

r

Dexter Studios R&D

Wanho Choi

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Light Spectrum

Light is composed of electromagnetic waves.

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Visible Spectrum

Not all these waves are visible to the naked human eye. (visible range: 380 nm ~ 780 nm)

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Color from Light

Isaac Newton’s experiment (1966)

Pure colors (or spectral colors) cannot split into more colors.

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Why does an apple appear red?

An apple absorbs the visual wavelengths and only reflects the red ones.

When this light enters the eye, the brain then perceives this stimulus as a color.

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Three Requirements for Color

light source

reflector (object)

sensor (eye)

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Color Perception

Light(빛) ➠ cornea(각막) ➠ retina(망막) ➠ light receptor(광수용체) ➠ optic nerve(시신경) ➠ brain(뇌) Color is the result of visual perception of light between 380 ~ 780 nm.

http://www.nanosysinc.com/dot-color-archive/2013/07/16/how-much-color-gamut-do-displays-really-need-part-2-how-we-perceive-color

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Color Perception

Human color perception is affected by various factors - Nearby colors (주변색)

- Adaptation to previous views (이전색에 대한 적응) - State of mind (인지시의 정신 상태)

http://www.psy.ritsumei.ac.jp/~akitaoka/shikisai2005.html

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Structure of Human Eye

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Photoreceptor Cells

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Photoreceptor Cells

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간상 세포 (rod cell) 원기둥 모양 (cylindrical shape) 평균 9천만개 (avg. 90,000,000 cells) 명암을 구별 (monochromatic vision) 약한 빛을 감지 (night-vision) 원추 세포 (cone cell) 원뿔 모양 (conical shape) 평균 6백만개 (avg. 6,000,000 cells) 색상을 구별 (color vision) 강한 빛을 감지 (day-vision)

Photoreceptor Cells

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Photoreceptor Cells

rods

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Photoreceptor Cells

rods

cones

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Three Types of Cone Cells

Each kind has a different spectral response.

http://en.wikipedia.org/wiki/Photoreceptor_cell http://www.achromatopsia.info/color-blindness/

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Three Types of Cone Cells

That is why we need three parameters (trichromatic values) to describe a color.

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Tristimulus Human Vision

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Tristimulus Human Vision

Each kind has a different spectral response.

- S-cone (β-cone) : short wavelength

- M-cone (γ-cone) : medium wavelength - L-cone (ρ-cone) : long wavelength

(# of S-cones) < (# of M-cones), (# of L-cones)

Luminance:

luminance (Y)

Y (

λ

)

= L(

λ

)

+ M (

λ

)

+ S(

λ

)

http://www.cyberphysics.co.uk/Q&A/KS5/medical/eye/Q7.html

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Tristimulus Human Vision

Sensitive to wavelengths from 380-780 nm

Yellow-green is perceived as being most luminous.

luminance (Y)

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Tristimulus Human Vision

Green wavelength of light appear to be lighter than similar amounts (photons) of blue or red.

luminance (Y)

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How do we see color?

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Colorimetry

The science of measuring colors

Measuring colors is difficult since every person sees color a little differently. So, colorimetry measures how an average person will see the color instead.

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Color Matching Experiment

A tedius series of experiments with actual human observers by Wright & Guild (respectively) Tristimulus concept based experiments

Three primaries: red (700 nm), green (546.1 nm), blue (435.8 nm)

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Color Matching Experiment

A tedius series of experiments with actual human observers by Wright & Guild (respectively) Tristimulus concept based experiments

Three primaries: red (700 nm), green (546.1 nm), blue (435.8 nm)

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Color Matching Experiment

Standard observer: average healthy person's sensitivity to lights and colors with 2° FOV Due to the non-even distribution of cones, the results depend on the observer's FOV.

Re-experiment (1964) with 10° FOV (most widely used today)

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Color Matching Experiment

Almost all colors can be visually matched by the combinations of three different lights.

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Color Matching Functions

At each wavelength, the ordinates show the amounts of the three primaries required by the standard observer to match a light of that wavelength.

The first defined quantitative link between physical pure colors (i.e. wavelengths) in the

electromagnetic visible spectrum, and physiological perceived colors in human color vision

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Color Matching Functions

In some cases, reddish tone is not vanished even thought red light is not used.

A negative amount of a certain primary is needed for a match. (just mathematically)

If C

≠ aR + bG + cB for all a,b,c ≥ 0

But, C

+ aR = bB + cC for any a,b,c ≥ 0

∴C = −aR + bG + cB for any a,b,c ≥ 0

http://en.wikipedia.org/wiki/CIE_1931_color_space

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CIE RGB vs CIE XYZ

Negative values are really hard to deal with! (It is impossible to set negative value for devices.) Another analytical matching functions needs to be developed with nowhere negative.

CIE 1931 XYZ CIE 1931 RGB

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CIE 1931 XYZ Color Space

The primary colors are not real colors (They cannot be generated with any light spectrum.) It encompasses all color sensations that an average person can experience.

It serves as a standard reference against which many other color spaces are defined.

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Meaning of X, Y, and Z

X

=

[

x (

λ

)

⋅ R(

λ

)

⋅ L(

λ

)

]

d

λ

380 780

Y

=

[

y(

λ

)

⋅ R(

λ

)

⋅ L(

λ

)

]

d

λ

380 780

Z

=

[

z (

λ

)

⋅ R(

λ

)

⋅ L(

λ

)

]

d

λ

380 780

R(λ): light energy from reflector L(λ): light energy from light source CIE XYZ spectral sensitivity

SIGGRAPH 2009 Courses: Color Imaging

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Meaning of X, Y, and Z

The mathematically reformulated tristimulus values with non-negative values

These values do not directly correspond to red, green, and blue, but are approximately so. Y: luminance factor (The Y-curve is similar to the luminous efficiency curve.)

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CIE xyY Color Space

3D XYZ color space → 2D xy color space with normalization and fixed Y coordinate

x

= X / (X +Y + Z)

y

= Y / (X +Y + Z)

z

= Z / (X +Y + Z)

∴ x + y + z = 1

xyY

chromaticity luminance (fixed as 100)

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CIE xyY Color Space

plane : x

+ y + z = 1

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CIE 1931 Chromaticity Diagram

Tongue-shaped or horseshoe-shaped figure

All of the visible spectrum to the average person Non-negative values of x and y

Spectral locus : curved edge (single wavelength colors) Line of purples: the straight edge on the lower part

White point: (x,y) = (1/3, 1/3)

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CIE 1931 Chromaticity Diagram

Line: all possible colors by mixing two colors

Triangle: all possible colors by mixing three colors

But, 0.5A+0.5B is not the midpoint of the line segment AB.

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MacAdam Ellipses

Indistinguishable color regions

A distance on the xy chromaticity diagram does not

correspond to the degree of difference between two colors.

Euclidean distance in x,y not a good metric for perceptual similarity.

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Metamerism

The same perceived color can be produced by different combinations of various colors.

Even though the spectral components of two lights are obviously different, to our eyes they may appear as the same color.

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Metamerism

Metamerism occurs when two samples appear identical under one set of viewing conditions, but not under another set of conditions. When this occurs, we call the two samples a

metameric pair.

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Cons of XYZ Color Space

Primaries are imaginary (non-intuitive)

One cannot build a display with such primaries. (almost possible, but expensive): impractical A lot of XYZ values which cannot correspond to physical colors: wasteful

Hence we cannot work with just CIE XYZ.

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Color Space

An abstract model which describes the range of colors A n-dimensional space (typically, n=3)

A useful method to understand the color capabilities of a particular digital device or file

- It represents what a camera can see, a monitor can display or a printer can print, and etc.

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Some Confusing Terms

Color model: a mathematical model describing the way colors can be represented as n-tuples

- RGB, CMYK, HSV, HSL, etc.

Color space: specific values for the primaries

- CIE XYZ, CIE LUV, sRGB, Adobe RGB, Apple RGB, REC. 709 RGB, ACES RGB, etc.

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RGB Color Model

R: red, G: green, B: blue An additive color model

It is easy to understand and use. A device-dependent color model

- Different devices detect or reproduce a given RGB value differently.

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RGB Cube

A RGB color model based 3D color space

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CIE Color Spaces

CIE 1931 XYZ (aka "CIE 1931”)

- The 1st color space based on measurements of human color perception, and the basis for almost all others

CIELUV

- A modification of "CIE 1931 XYZ" to display color differences more conveniently

CIELAB (or L*a*b* or Lab)

- The more linear color space than others. Perceptually linear means that a change of the same amount in a color value

should produce a change of about the same visual importance.

CIEUVW

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sRGB Color Space

A color space developed by both HP and Microsoft in 1996 s: standard

Standard color space for monitors, printers, and the internet

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Adobe RGB Color Space

An RGB color space developed by Adobe Systems, Inc. in 1998 To supplement for cyan-green loss in sRGB

It was designed to encompass most of the colors achievable on CMYK color printers. Adequate for representing green forest, blue sky, etc.

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sRGB vs Adobe RGB

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Color Gamut

A subset of colors which can be represented within a given color space or by a device

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Color Gamut Comparison

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Raw File

A original file produced by a digital sensor (camera, scanner, etc.) Untouched raw information

No compressed, no encoding, so no data loss

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Color Depth

http://photography.tutsplus.com/articles/bit-depth-explained-in-depth--photo-8514 http://www.theasc.com/magazine/april05/conundrum2/image11.html

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Color Depth

https://documentation.apple.com/en/finalcutpro/usermanual/index.html#chapter=52%26section=7%26tasks=true https://jackhaywood.wordpress.com/y12/new-media/unit-19/raster-vs-vector/

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Gradation vs Dynamic Range

Gradation: the gradual change between the largest and smallest values Dynamic range: the ratio between the largest and smallest values

poor gradation rich gradation high dynamic range low dynamic range

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Scene-Referred vs Output-Referred

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Scene-Referred vs Output-Referred

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A transformation from scene-referred to output-referred

Tone Mapping

HDRI

LDRI

LDR

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Linearity

Additivity

Homogeneity

f(x

+ y) = f(x) + f(y)

f(ax)

= af(x) for all a

It’s predictable!

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Gamma

Non-linear relationship between input and output

V

out

= V

in

γ

http://www.dfstudios.co.uk/articles/programming/image-programming-algorithms/image-processing-algorithms-part-6-gamma-correction/

γ

< 1

γ

= 1

γ

> 1

1 1 0 0

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Non-linear Human Vision

Human eyes do not respond linearly to light.

- The human eye is more sensitive to small variation of light in a dark environement than in a bright one (Weber’s law)

Digital sensors (digital cameras) respond linearly to light.

- When twice the number of photons hit the sensor, it receives twice the signal.

http://www.cambridgeincolour.com/tutorials/gamma-correction.htm http://www.peachpit.com/articles/article.aspx?p=1709190&seqNum=3

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Gamma Encoding

A technique to optimize the usage of bits when encoding an image using logarithm

Use more bits for dark range!

Gamma encoded image: .jpg, .tiff, etc.

Gamma compression

http://www.cambridgeincolour.com/tutorials/gamma-correction.htm http://www.wildlifeinpixels.net/blog/gamma-encoding/

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Non-linear Output Device

60

128

100

160

200

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Non-linear Output Device

Output devices (CRT/LCD monitors, prints) also have non-linearity in their color response. Every monitor has different response curve.

RGB(128,128,128) is not half as bright as RGB(255,255,255).

http://filmicgames.com/archives/299 http://filmicgames.com/archives/299

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Gamma Correction

Gamma encoding was developed to compensate for the

input–output characteristic of monitors.

Altering the input signal by gamma compression can

cancel this nonlinearity (monitor transfer function).

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Gamma Correction

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Linear Workflow

Most of renderer works in linear space internally.

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Linear Workflow

Most of renderer works in linear space internally.

Most of texture images are stored using non-linear encoding (gamma applied).

wrong

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Linear Workflow

Most of renderer works in linear space internally.

Most of texture images are stored using non-linear encoding (gamma applied).

right

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Color Management

food industry

retail

media

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Color Management

Color pipeline: a set of color transformations

Well-defined color pipeline = rigorous transformation at each stage Goal

- The seamless intercutting of VFX and non-VFX shots

- The consistent color across a range of devices within a pipeline

During the visual effects process, the display transform is never baked

into the imagery except for “throw-away” deliveries such as editorial output or rough preview screenings.

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Color Management

R 205 G 012 B 005 R 205 G 012 B 005 R 205 G 012 B 005 device 1 device 2 source device R ? G ? B ? R 205 G 012 B 005 device 2 source device

Introduction to Color Management for Film and TV

R 205 G 012 B 005

device 1 device 2

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Color Space Transform

A transformation between two different color spaces (color space conversion)

R

= aR + bG + cB

G

= dR + eG + fB

B

= gR + hG + iB

R

G

B

=

a b

c

d

e

f

g h

i

R

G

B

linear color space linear color space

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Color Space Transform

A transformation between two different color spaces (color space conversion)

Since a color space conversion may cause some errors such as distortion, interpolation,

clipping, round-off, etc, you must minimize the use of color space.

R

= aR + bG + cB

G

= dR + eG + fB

B

= gR + hG + iB

R

G

B

=

a b

c

d

e

f

g h

i

R

G

B

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Some Transformation Matrices

The RGB values must be linear and in the nominal range [0.0, 1.0].

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CIE Standard Illuminant D65

One of the commonly used standard illuminants defined by CIE (white point: 6500 K) D series: standard illumination conditions at open-air in different parts of the world Midday sun in Western Europe / Northern Europe (daylight illuminant)

There are no actual D65 light sources, only simulators.

D65 should be used in all colorimetric calculations requiring representative daylight unless there are specific reasons for using a different illuminant.

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CIE Standard Illuminant D65

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CIE Standard Illuminant D65

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Color Temperature

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LUT

Look-Up Table (pre-calculated sets of data)

An excellent technique for optimizing the evaluation of functions that are expensive to compute and inexpensive to cache

For data requests that fall between the table's samples, an interpolation algorithm can generate reasonable approximations by averaging nearby samples.

y

= x

3

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LUT

Directly applying multiple sophisticated color transforms to high-resolution imagery is heavy.

Consider an analytical color operator, f(x), applied to an 8-bit grayscale image. The naive implementation would be to evaluate f(x) for each pixel.

However, one may observe that no matter how complex the function, it can evaluate to only one of 255 output values (corresponding to each unique input).

Thus, an alternate implementation would be to tabulate the function's result for each possible input value, then to transform each pixel at runtime by looking up the stored solution.

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LUT in Color Correction Pipeline

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LUT in Color Correction Pipeline

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LUT in Color Correction Pipeline

LUTs are also useful when wanting to separate the calculation of a transform from its application. For example, in color pipelines it is often useful to bake a series of color

transforms into a single lookup table, which is then suitable for distribution and re-use, even in situations where the original data sets are not appropriate for distribution.

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ACES

Academy Color Encoding System (or Space, or Specification)

A color image encoding system proposed by the Academy of Motion Picture Arts & Sciences

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Why ACES?

Until recently moving a project between facilities often resulted in color changes caused by

different display devices or even a number of the same devices calibrated differently. Also a

look developed result would be viewed differently when played on new display devices. This is a fact of life in many workflows today and results in much time and effort spent to cope with

these color issues.

Additionally there are new display devices appearing all the time. Flat panels, projectors and laser imaging devices all have different colorimetric properties and the list keeps growing.

Program producers quite correctly want to future-proof their projects and retain their artistic vision on any future display device.

ACES is designed to eliminate these issues making high-end post more efficient today and allowing easier use of content in the future on new display devices.

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Academy Color Encoding Specification

A scene-referred image format with standard, future-proof color space

A very wide color gamut (R,G,B values exceed the human visible range.) Fixed middle gray point: (0.18, 0.18, 0.18)

When stored on disk, no gamma (or log) is pre-applied

A unification of scene-linear floating-point HDR workflows (16-bit half-precision) A constrained, or limited, version of the OpenEXR file format with extra metadata The only allowable channel layouts are stereo and non-stereo RGB(A).

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Academy Color Encoding Space

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ACES Workflow

ACES enables consistent color rendition in pipelines including any combination of ACES

compliant cameras, processing and display devices both now and in the future.

ACES

space

various

input

various

output

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ACES Workflow

ACES enables consistent color rendition in pipelines including any combination of ACES

compliant cameras, processing and display devices both now and in the future.

ACES

space

various

input

various

output

IDT RRT/ODT CGI

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ACES Workflow

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ACES Workflow

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ACES Workflow: IDT

Input Device Transform

Conversion from cameras, scanners, or other image sources to ACES

Academy Color Encoding Specification: linear RGB 16-bit floating-point format

- It remove any capture characteristics that relate to the camera, lens, sensor, or recording method and as accurately as

possible reproduce the physical light of the scene.

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ACES Workflow

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ACES Workflow: ACES

With conceptually unlimited gamut and dynamic range

ACES color space is great for doing mathematical operations in. It is almost impossible to hit the walls and clip or limit color.

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ACES Workflow: LMT

Look Modification Transform Optional

Once images are in ACES color space, the LMT provides a way to customize a starting point for color correction. The LMT doesn't change any image data whereas an actual grade works directly on the ACES pixels. An example of a LMT would be a “day for night” or “bleach

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ACES Workflow

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ACES Workflow: RRT

Reference Rendering Transform

Conversion from ACES (scene-referred) to OCES (output-referred)

- OCES: The output referred color space created by applying the RRT to ACES. It is still an idealized color space, and needs

an ODT to look correct on any real world display.

It accommodates for the difference between outdoor and cinema viewing environments. It applies color adjustments associated with pleasing image reproduction.

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ACES Workflow: ODT

Output Device Transform

ODTs maps the image from the high dynamic range of OCES to an ideal display format such as Rec. 709.

ODTs are applied to prepare the images for display on other devices. Each display standard will need its own ODT.

As with IDTs, the ODTs may be supplied by device vendors, software vendors, and AMPAS itself.

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OCIO

OpenColorIO

An open-source color pipeline created sponsored by Sony Picture Imageworks (SPI)

It enables color transforms and image display to be handled in a consistent manner across

multiple graphics applications in cinematic color pipeline.

New profiles are easily created from the atomic operators common to post-production color

processing (1D LUTs, 3D LUTs, HDR processing conversions, etc), and can then be used (and shared) just as easily as the included defaults.

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