Computer Graphics. Rendering. Rendering 3D. Images & Color. Scena 3D rendering image. Human Visual System: the retina. Human Visual System

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Rendering Rendering 3D Scena 3D rendering image Computer Graphics Università dell Insubria Corso di Laurea in Informatica Anno Accademico 2014/15 Marco Tarini Images & Color M a r c o T a r i n i C o m p u t e r G r a p h i c s 2 0 1 4 / 1 5 U n i v e r s i t à d e l l I n s u b r i a 5 Human Visual System Human Visual System: the retina M a r c o T a r i n i C o m p u t e r G r a p h i c s 2 0 1 4 / 1 5 U n i v e r s i t à d e l l I n s u b r i a 8 1

Human Visual System Human Visual System Cones 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 2

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 HSL and HSV 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: Colors described in terms of Hue Base color Saturation Pureness of the color Lightness Intensity HSV: Lightness is substituted by Value 3

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 = V γ Gamma correction changes the value of γ Image Representations Vector Images: Example 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 4

Raster Images Raster Image: gray scale 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 Images: resolution Raster Images: alpha channel 10x19 20x37 38x70 158x300 5

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 6

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) Rarter Images: metadata Exif -- Exchangeable image file format date camera settings thumbnail description copyright geolocation (GPS coords) M a r c o T a r i n i C o m p u t e r G r a p h i c s 2 0 1 4 / 1 5 U n i v e r s i t à d e l l I n s u b r i a 30 M a r c o T a r i n i C o m p u t e r G r a p h i c s 2 0 1 4 / 1 5 U n i v e r s i t à d e l l I n s u b r i a 31 7