Rendering
• Rendering 3D
Scena 3D
renderingimage
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Computer Graphics
Images & 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
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 for Additive primaries systems, such As 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
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
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 158x300 20x37
10x19
Raster Images: alpha channel
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
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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