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Rendering

• Rendering 3D

Scena 3D rendering image

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Computer GraphicsImages & Color

Università dell’Insubria

Corso di Laurea in Informatica

Anno Accademico 2014/15

Marco Tarini

Human Visual System Human Visual System: the retina

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Human Visual System

• Cones

Human Visual System

• Composed of:– Eyes Capture the light and sends signal to Brain– Brain Interprets the signal received from the Eyes

• Visible Light– Wave length between 380 and 780 nm– Infrared, Microwave > 780,– Ultraviolet, X-Ray < 380

• Retina composed of: Rods & Cones• Rods:

– More sensible to small amounts of light – Monochrome– MANY! ~120 Mega

• Cones:– Less sensible– Fewer ~8 Mega. Concentrated in “fovea”.– Three kinds (Long Medium Short): differentiate light wavelenght!

Color Spaces : Primary Colors

Additive Subtractive

Color Spaces

• Difficult to define a representation that is valid for all• All representations use 3 primary colors (as the eye):

colors represented as combinations of them• Two models: Additive Subtractive• Additive: all colors represented as the sum of the

intensity of 3 basic colors, by combining all colors we obtain white. For example: LCD screens, Lights

• Subtractive: each component blocks the opposite color (cyan is the complement of red), by combining all colors we obtain black. For example, Printers, Crayon colors

Interactive Graphics: Color and Images

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CIE RGB and XYZ

• Very important standard representation • experimentally defined by CIE.• Based on 3 color-matching functions (r, g, b)

CIE XYZ

• Equivalent representation using only positive values

Device–dependent color space

• The Color-space of a device depends on its physical limitations.

• GAMUT is the set of all colors that a device can output

• Examples of GAMUTs forAdditive primaries systems, suchAs NTSC, Adobe RGB, sRGB(used by HP and Microsoft)

HSL and HSV

• HSL: Colors described in terms of– Hue

• Base color– Saturation

• Pureness of the color– Lightness

• Intensity

• HSV: Lightness is substituted by Value

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Representation change and Illuminant

• Possible to convert between RGB and HSL/HSV representations

• Conversions depend on the Illuminant (spectrum of the light source). CIE XYZ standardized the spectrum defining a number of standard illuminants– Illuminant A corresponds to average incandescent light, B to

direct sunlight• More information at http://brucelindbloom.com/

CIELab and Gamma

• CIELab is a Color space defined by CIE in 1976 using:– L* Lightness– a* and b* Chromaticity

• Euclidean distance between two points correlates very well with human perception of similarity/distance between colors

• In CRT monitors, RGB intensity I is proportional to voltage V as follows I = Vγ

• Gamma correction changes the value of γ

Image Representations

• Images can be represented in several ways, the most common ones are

• Vector images– Image = set of drawing primitives

• Raster images– image = regular 3D gird of small colored tiles

Vector Images: Example

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Raster Images

• Image defined as a set of pixels (picture elements) aligned in a rectangular shape.

• Size is the number of horizontal and vertical lines (For example, 640*480)

• Pixels defined by a scalar value (grayscale images) or an array of (usually 3) scalar values (color images)– pixel depth = how many bits per pixel

• The length of the vector defines the number of channels. Most raster images use 4 channels, called red, green, blue and alpha, where the fourth channel alpha is used to handle transparency.

Raster Image: gray scale

Raster Images: resolution

38x70 158x30020x3710x19

Raster Images: alpha channel

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Raster Images: dynamic range

• Ratio between highest and lowest value• HDRI – High Dynamic Range Images

Pros and Cons

• Vector images automatically adapt to the resolution of the device.

• Well suited for computer-generated images such as logos, trademarks, diagrams, stylized drawings and other similar images.

• Raster images well suited for natural images (photos and others).

• Quality of raster images depends on image resolution

Vector Images: common formats

• SVG: – XML-based – developed by W3C – basic shapes, text, colors, patterns …

• PostScript (PS): – printers – high quality printing of images– includes ink control

• Portable Document Format (PDF)– by Adobe– includes subsets of PS

Rarter Images: common formats

• PNG (Portable Network Graphics): – lossless compression– many formats, including: 3 or 4 channels– good for synthetic images

• JPEG (Joint Photographic Experts Group): – (typically) lossy compression (DCT: discrete cosine transform)– 3 channels 8 bits– good for natural images (digital photography)– advancemet: JPEG 2000

• GIF (compuserve)– strange quirk of image format history– used for tiny animations

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Rarter Images: not so common formats

• TIFF – (typically) lossless, – hi-dynamic range data– hi-quality digital photography

• PNM (portable any map)– not very used– but… trivial to parse (ASCII)

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Rarter Images: metadata

• Exif -- Exchangeable image file format– date– camera settings– thumbnail– description– copyright– …– geolocation (GPS coords)

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