Computer Graphics (CS 563) Lecture 4: Advanced Computer Graphics - PowerPoint PPT Presentation

Computer Graphics (CS 563) Lecture 4: Advanced Computer Graphics Image ‐ Based Effects: Part 2 Prof Emmanuel Agu Computer Science Dept. Worcester Polytechnic Institute (WPI)

Image Processing  Graphics concerned with creating artificial scenes from geometry and shading descriptions  Image processing  Input is an image  Output is a modified version of input image  Image processing operations include altering images, remove noise, super ‐ impose images

Image Processing  Example: Sobel Filter Original Image Sobel Filter

Image Processing  Image processing the output of graphics rendering is called post ‐ processing  To post ‐ process using GPU, rendered output usually written to offscreen buffer (e.g. color image, z ‐ depth buffer, etc)  Image in offscreen buffer treated as texture, mapped to screen ‐ filling quadrilateral  Pixel shader invoked on each element of texture

Image Negative  Another example

Image Distortion

Image Sharpening

Embossing

Toon Rendering

Toon Rendering for Non ‐ Photorealistic Effects

Blurring  For some operations, texture element may be combined with neighboring texture elements (blurring) Without motion blur With motion blur

Texture Animation using Image Processing  Use GPU to modify textures from frame to frame  Animations such as fluid flow can be done this way  Example: simulating rain by Tatarchuk et al

Heat Shimmer

Color Correction  Color correction uses a function to convert colors in an image to some other color  Why color correct?  Mimic appearance of a type of film  Portray a particular mood  Convert from one color space to another  Example of conversion from RGB to CIE’s XYZ color space       X 0 . 412453 0 . 357580 0 . 180423 R              Y 0 . 212671 0 . 715160 0 . 072169 G             Z 0 . 019334 0 . 119193 0 . 950227 B

Color Correction

Color Correction

High Dynamic Range  Sun’s brightness is about 60,000 lumens  Dark areas of earth has brightness of 0 lumens  Basically, world around us has range of 0 – 60,000 lumens (High Dynamic Range)  However, monitor has ranges of colors between 0 – 255 (Low Dynamic Range)  New file formats have been created for HDR images (wider ranges). (E.g. OpenEXR file format)

High Dynamic Range  Some scenes contain very bright + very dark areas  Using uniform scaling factor to map actual intensity to displayed pixel intensity means:  Either some areas are unexposed, or  Some areas of picture are overexposed Under exposure Over exposure

Tone Mapping  Process of scaling intensities in real world images (e.g HDR images) to fit in displayable range  Try to capture feeling of real scene: non ‐ trivial  Example: If coming out of dark tunnel, lights should seem bright

Types of Tone Mapping Operators  Global: Use same scaling factor for all pixels  Local: Use different scaling factor for different parts of image  Time ‐ dependent: Scaling factor changes over time  Time independent: Scaling factor does NOT change over time  Real ‐ time rendering usually does NOT implement local operators due to their complexity

Tone Mapping Operators

Simple (Global) Tone Mapping Methods

Tone Mapping  If range of input values is small, compute average then scale so that average in displayable range  Simple average may cause a few large values to dominate  Reinhard suggested to use logarithm instead when summing pixel values   1       L exp log( L ( x , y ))   w w  N  x , y  is the log ‐ average luminance, avoids log of 0  L w is the luminance at pixel (x,y)  L w ( x , y )

Tone Mapping  Once log ‐ average luminance is computed, can then define tone mapping operator a  ( , ) ( , ) L x y L x y w L w is resulting luminance L ( x , y )   a parameter is key of the scene (a = 0.18 is normal)  High key minimizes contrasts and shadows. E.g. a = 0.72  Low key maximizes contrasts between light and dark. E.g. a = 0.045

Tone Mapping: Effects of a

Lens Flare and Bloom  Caused by lens of eye/camera when directed at light  Halo – refraction of light by lens  Ciliary Corona – Density fluctuations of lens  Bloom – Scattering in lens, glow around light Halo, Bloom, Ciliary Corona – top to bottom

Lens Flare and Bloom  Use set of textures for glare effects  Each texture is bill boarded  Alpha map – how much to blend  Can be given colors for corona  Overlap all of them !  Animate – create sparkle

Depth of Field  In photographs, a range of pixels in focus  Pixels outside this range are out of focus  This effect is known as Depth of field

Depth of Field using Accumulation Buffer  Jitter view position, add weighted samples to accumulation buffer  After multiple rendering passes, display picture  Downside: Multiple rendering passes is expensive

Depth of Field using Scattering  Scatter shading value of each location on a surface to neighboring pixel  Sprites used to represent circles of influence  Pixel value is averaged sum of all overlapping circles

Motion Blur  Antialiasing is spatial blurring  In cameras, caused by exposing film to moving objects  Motion blur: Blurring of samples taken over time  Makes fast moving scenes appear less jerky  30 fps + motion blur better than 60 fps + no motion blur

Motion Blur  Accumulation buffer can be used to create blur  Basic idea is to average series of images over time  Move object to set of positions occupied in a frame, blend resulting images together

Motion Blur  Can blur moving average of frames. E.g blur 8 images  When you render frame 9, subtract frame 1, etc  Velocity buffer: blur in screen space using velocity of objects

Fog  Fog was part of OpenGL fixed function pipeline  Using shaders, fog applied to scene just before display  Shaders can generate more elaborate fog  Fog is atmospheric effect  A little better realism  Help in determining distances

Fog example  Often just a matter of  Choosing fog color  Choosing fog model  Turning it on

Rendering Fog  Color of fog: color of surface: c c s f     f ( 1 f ) f [ 0 , 1 ] c c c p f s  How to compute f ?  3 ways: linear, exponential, exponential-squared  Linear:  z z  end p f  z z end start

Fog   d f z f e p  Exponential  2  ( d f z )  Squared exponential f e p  Exponential derived from Beer’s law  Beer’s law: intensity of outgoing light diminishes exponentially with distance

Fog  f values for different depths can be pre ‐ computed and stored in a table on GPU  Distances used in f calculations are planar  Can also use Euclidean distance from viewer or radial distance to create radial fog

Different Atmospheres More generally, we can simulate better skies

Volume Rendering  Volumetric data is represented as volumetric pixels (voxels)  Rendering Voxels (CT/MRI)  Methods  Implicit surface techniques to convert voxel samples into polygonal surfaces (called isosurfaces)  Voxel Data as set of 2D image slices (Lacroute & Levoy)  Splatting – Voxel represented by alpha blended circular object (splat) , that drops of in opacity at fringes  Volume slices as textured Quads (OpenGL Volumizer API)

Volumetric Texturing  Represent objects as sequence of semi ‐ transparent textures  Good for rendering fuzzy or hairy objects

References  Kutulakos K, CSC 2530H: Visual Modeling, course slides  UIUC CS 319, Advanced Computer Graphics Course slides  David Luebke, CS 446, U. of Virginia, slides  Chapter 2 of RT Rendering  Suman Nadella, CS 563 slides, Spring 2005