The computer image

The three main fields of computer imagery - Computer graphics, image, Processing and Computer vision - are merging in many applications. Computer Vision techniques are used in computer graphics to collect and model complex scenes; computer graphics techniques are used to constrain the recognition of 3D objects by computers; image processing techniques are routinely used by graphic designers to manipulate photographs. For the first time this textbook brings all three areas together in a coherent overview.

Special features

Unique breadth of coverage of subjects that have previously only appeared in separate texts.
Novel treatment of the moving image, Virtual reality, medical imaging and computer art.
Packaged with the book is a CD-ROM that provides implementations of many of the techniques described in the book.
The CD-ROM contains scene files, animation demonstrations, a complete set of all the images used in the book and a suite of programs.
The software can be used for teaching, experimentation and the development of an application package.
The source code is written in C++.
The software includes a Z-buffer renderer, a distributed ray tracer, a radiosity renderer, an image processing module containing all the normal filtering facilities and transforms, morphing and warping software particle/elastic object simulation with collision detection, a progressive image compressor using wavelets (including a Java, ActiveX, OLE, 3DSMAX plugin), stereo and autostereogram generator, modeling software (including a Bezier modeller and a rnesh optimizer), computer vision software including depth from stereo, (low field estimation, object tracking and classification of satelliteimagery.

Table of contents

Preface
Acknowledgements
Dedication
1 The computer image -- an overview
1.1 The nature of a computer image
1.2 Synthesizing images or computer graphics
1.2.1 Computer graphics and its impact
on popular culture and art
1.2.2 Computer graphics and its practitioners
General reading in computer graphics
1.3 Image processing -- an overview
General reading in image processing
1.4 Computer vision
General reading in computer vision
2 Representation and modelling of three-dimensional objects
2.1 Introduction
2.2 Polygonal representation of three-dimensional objects
2.2.1 Creating polygonal objects
2.2.2 Manual modelling of polygonal objects
2.2.3 Automatic generation of polygonal objects
2.2.4 Mathematical modelling of polygon objects
2.2.5 Generating polygon objects by sweeping
2.3 Representation of objects using bicubic parametric patch nets
2.3.1 Creating objects with bicubic parametric patch nets
2.4 Constructive Solid Geometry (CSG) representation of objects
2.5 Space subdivision techniques for object representation
2.5.1 Creating voxel objects
2.6 Representing objects with implicit functions
2.7 Rendering strategies and representations
2.7.1 Rendering polygon objects
2.7.2 Rendering a parametric patch net
2.7.3 Rendering a CSG description
2.7.4 Rendering a voxel description
2.7.5 Rendering implicit functions
2.8 Summary
Further reading
3 Basic realism -- lighting polygon objects
3.1 Introduction
3.2 An overview of the rendering process
3.3 Rasterization of a polygon
3.4 Hidden surface removal
3.4.1 Culling
3.4.2 Z-buffer algorithm
3.5 Shading pixels
3.5.1 Local reflection models
3.5.2 Practical points
3.5.3 Light source considerations
3.6 Interpolative shading techniques
3.6.1 Gouraud shading
3.6.2 Phong shading
3.6.3 Renderer shading options
3.6.4 Bi-linear interpolation
Further reading
4 Increasing realism -- textures and shadows
4.1 Texture mapping -- what aspects of the
object to modulate
4.2 Two-dimensional textures and three-dimensional objects
4.2.1 Polygon mesh texture mapping:
two-part mapping
4.2.2 Two-dimensional texture domain
techniques: mapping onto bicubic parametric patches
4.3 Three-dimensional texture domain techniques
4.4 Bump mapping
4.5 Environment mapping
4.6 Anti-aliasing and texture mapping
4.7 Interactive techniques in texture
mapping
4.8 Adding shadows in rendering
4.8.1 Computer graphics and shadows
4.8.2 Shadow mapping or the shadow Z-buffer
4.8.3 Anti-aliasing and the shadow Z-buffer
Further reading
5 Increasing realism -- the evolution of
local reflection models
5.1 Perfect reflection models
5.2 Perfect diffuse -- empirically spread specular (Phong)
5.3 Physically based specular reflection
(Blinn, Cook and Torrance)
5.3.1 Modelling the micro-geometry of the surface
5.3.2 Shadowing and masking effects
5.3.3 Viewing geometry
5.3.4 Electromagnetic effects
5.4 Pre-computing BRDFs
5.5 Physically based diffuse component
5.6 Further reading
6 Increasing realism -- global illumination
or following the light
6.1 The evolution of global illumination algorithms
6.1.1 Whitted ray tracing
6.1.2 Distributed ray tracing
6.1.3 Two-pass ray tracing
6.1.4 Radiosity
6.2 Towards L(DIS)*E
6.2.1 Extending radiosity
6.2.2 Path tracing
6.2.3 The RADIANCE renderer
6.3 Whitted ray tracing -- the details
6.3.1 Tracing rays -- initial
considerations
6.3.2 Inclusion of a local reflection
model
6.3.3 Shadows are easy
6.3.4 Hidden surface removal is easy
6.3.5 Using recursion to implement ray tracing
6.3.6 The adventures of seven rays -- a ray tracing study
6.3.7 Ray tracing polygon objects --
interpolation of a normal at an
intersection point in a polygon
6.3.8 Bounding objects with simple shapes
6.3.9 Secondary data structures
6.4 Further developments in ray tracing
illumination model
6.4.1 Distributed ray tracing
6.4.2 Generalizing the trace direction
-- two-pass ray tracing
Further reading
6.5 Classical radiosity
6.5.1 Radiosity theory
6.5.2 Form factor determination
6.5.3 Increasing the accuracy
6.5.4 Seeing a partial solution -- progressive refinement
Further reading
7 Bicubics and image synthesis
7.1 Introduction
7.2 Bezier and the secret curves
7.3 From curves to surfaces
7.4 Modelling with Bezier patches
7.4.1 Joining Bezier curve segments
7.4.2 Joining Bezier surface patches
7.4.3 Modelling and interaction with Bezier patches
7.5 Patch CAGD example
7.6 Deriving a net of patches from an
object -- surface fitting
7.7 Rendering parametric surfaces
7.7.1 Approximation to a surface patch
using a polygon mesh
7.8 From patches to objects
7.9 Further reading
8 Defects in computer graphics images
8.1 Introduction -- the difficulty of
categorization
8.2 Sampling and image synthesis
8.3 The ultimate -- filtering a continuous
image
8.4 Supersampling -- the best filtering we
can do
8.5 Sampling and algorithms
8.6 Non-uniform sampling -- some
theoretical concepts
8.7 Comparative image study
8.7.1 Local reflection models
8.7.2 Texture and shadow mapping
8.7.3 Ray tracing
8.7.4 Radiosity
Further reading
9 Image processing for enhancement or basic
processing in image space
9.1 Pixel processing
9.1.1 Intensity transformations
9.1.2 Intensity level slicing
9.1.3 Intensity level to colour -- pseudo-colour enhancement
9.1.4 Image histograms and their uses
9.1.5 Histogram equalization
9.1.6 Image subtraction
9.1.7 Image smoothing
9.1.8 Sharpening or detail enhancement
9.1.9 Colour and image processing
9.2 Transforming the position of pixels --
image warping
9.2.1 Forward mapping
9.2.2 Inverse mapping
9.2.3 Two-pass transforms
9.2.4 The bottleneck problem
Further reading
10 Edges and their detection
10.1 The origin and nature of edges
10.2 Edge detection
10.2.1 Edge detection using difference operators
10.2.2 Detecting edges of predefined orientation
10.2.3 Edge masks with `combined' properties
10.2.4 Edge linking or aggregation
10.2.5 Local edge linking
10.3 Global processing and the Hough transform
10.3.1 Hough transform -- brute force
implementation
10.3.2 Hough transform -- O'Gorman and
Clowes
10.3.3 Hough transform -- circles
10.4 Edges and segmentation -- explicit
edge detection or boundary following
10.5 Further reading
11 Image transforms
11.1 The Fourier transform of images
11.1.1 Image processing and the Fourier
domain
11.1.2 Low pass filters
11.1.3 High pass filters
11.2 Other Fourier domain filtering techniques
11.2.1 Inverse filtering or deconvolution
11.3 The Discrete Cosine Transform (DCT)
11.4 Image pyramids
11.4.1 Wavelet transform
11.5 Image transforms and basis matrices
Further reading
12 Image segmentation
12.1 Segmentation -- grey scale thresholding
12.1.1 Thresholding multi-band or colour
images
12.1.2 Thresholding and approximate
boundary information
12.2 Using pixel properties other than
intensity -- texture-ba