| Algorithms | The Image Processing and Measurement Cookbook by Dr. John C. Russ www.reindeergraphics.com/tutorial/index.shtml Conference Papers Computer Vision Source Code Algorithms Basic image processing demos showing some basic image processing filters: thresholding, Gaussian filter, and Canny edge detector using MATLAB. Gaussian Masks, Scale Space and Edge Detection The SUSAN algorithms cover image noise filtering, edge finding and corner finding. Vision Systems Course Various Simple Image Processing Techniques Algorithms commonly used in spectral processing methods Beyond Photography — The Digital Darkroom |
| Alpha blending | pp. 150-154, High Performance Computer Imaging |
| Antialiasing | Aliasing and Antialiasing www.education.siggraph.org/slides/slides93/28_93.htm Antialiasing with Line Samples |
| Anti-vignetting | http://starmatt.com/articles/av.html |
| Area | efg’s Polygon Area and Centroid Lab Report |
| Astrophotos | Post-Processing Astrophotos How to Put the Astro in Photographer Star Shaping |
| Authentication | Image Authentication for a Slippery New Age, Dr. Dobb’s Journal, April 1995. www.ddj.com/articles/1995/9504/9504a/9504a.htm |
| Bar Codes | Introduction to Bar Coding www.taltech.com/resources/intro_to_bc/introbc.htm |
| Biometrics | Intelligent Biometric Techniques in Fingerprint and Face Recognition (book)
Also see Recognition, Faces and Recognition, Fingerprints below. |
| Books | Digital Image Processing Algorithms and Applications US UK DE |
| Centroid | efg’s Polygon Area and Centroid Lab Report Also see “Moments of Inertia” below |
| Chain Codes | 7. Processing Line Drawings http://cgm.cs.mcgill.ca/~godfried/teaching/pr-web.html |
| Chromaticity Charts | efg’s Color Reference Library |
| Classification | Jean Vezina’s automatic tree species identification from digitized aerial photographs. PowerPoint presentation for forestry audience, TreeID.ZIP. Abstract.
Fourier Descriptors Allow Web-Inspection System to Classify Plastic Shapes Image Processing and Neural Networks Classify Complex Defects Chapter 17, Classification, pp. 509-520 |
| Compression | Image Compression, pp. 179-215 Digital Image Processing: Principles and Applications Image Compression, Chapter 9 Compression Links Chapter 6, Image Compression, pp. 307-412 Chapter 9, Image data compression, High Performance Computer Imaging Mitsuharu ARIMURA’s Bookmarks on Source Coding/Data Compression |
| Condensation | The Condensation Algorithm www.dai.ed.ac.uk/CVonline/LOCAL_COPIES/ISARD1/condensation.html |
| Contrast | Contrast Stretching, pp. 54-59 Simplified Approach to Image Processing Contrast Perception efg’s HistoStretchGrays Lab Report Contrast Manipulation, pp. 228-232 Also see Histograms below. |
| Counting Peaks | Algorithm for counting peaks on chart efg’s UseNet Post efg’s Pixel Profile Lab Report |
| Deconvolution | Deconvolution, Fourier-Self www.galactic.com/Algorithms/deconvle_fs.htm Blind Deconvolution Page |
| De-mosaicing | Digital Camera Designers Face a Maze of Trade-Offs www.eetimes.com/news/98/1003news/digital_camera.html |
| Detection, Buildings | Building Detection in Aerial Images www.imm.dtu.dk/documents/users/bro/thesis.abstract.html |
| Detection, Corners | The SUSAN algorithms cover image noise filtering, edge finding and corner finding. www.fmrib.ox.ac.uk/~steve/susan |
| Detection, Edges | Edge Detection, pp. 79-85 Simplified Approach to Image Processing A New Method of Edge Detection 3. Differentiation, Sharpening, Enhancement, Caricatures and Shape Morphing Evaluation of Subpixel Line and Edge Detection Precision and Accuracy Contour Extraction Edge Detection Canny Edge Detector Code The Canny Edge Detector Edges — The Canny Edge Detector “An Imaging Edge: Tips and Technique for Edge Extraction” Understanding Edge- and Line-Based Segmentation “Data Structures: Your Mind Doesn’t Process Pixels, so why Should Your Software?” J.F. Canny, “A computational approach to edge detection”, IEEE Patt. Anal. Sobel Masks for Edge Detection Line and edge detection: One simple test image The SUSAN algorithms cover image noise filtering, edge finding and corner finding. Edges: The Occurrence of Local Edges Chapter 1, Advanced Edge-Detection Techniques Chapter 12, Edges and Lines, pp. 387-413 pp. 177-179, High Performance Computer Imaging |
| Distortion | Eliminating Distortion in Your Imaging System www.edmundoptics.com/techsup/pdf/elim-distortion.pdf Nonlinear Lens Distortion |
| Dithering | Gernot Hoffmann’s “Dithering + Halftoning” (includes Hilbert-Peano dithering, Floyd-Steinberg dithering) www.fho-emden.de/~hoffmann/hilb010101.pdf Floyd-Steinberg Dithering Average, Floyd-Steinberg, Ordered, Random Dithering Test Page for Color Map Quantization (including Floyd-Steinberg error diffusion) Halftoning “A Balanced Dithering Technique,” December 1998, C/C++ Users Journal “Classic” dithering notes by Lee Cocker |
| Encryption / Decryption | efg’s ImageCrypt Lab Report |
| Enhancement | “Understanding Image Enhancement” median filter, rank filter, Nagao filter (edge-enhancement and image smoothing), Weymouth/Overton filter, contrast enhancement Vision Systems Design, July 1998, pp. 23-25; August 1998, pp. 21-24 Chapter 4, Image Enhancement, pp. 227-304 Chapter 4, pp. 161-251 |
| Erosion | Dr. John Russ’ UseNet Post about erosion Also see Skeletonization Erosion and Dialation, pp. 129-135 |
| Feature Extraction | Digital Image Processing: Principles and Applications, pp. 153-167 |
| Filters | Digital Filters www.dai.ed.ac.uk/HIPR2/filtops.htm “Understanding Image-Filtering Algorithms” Chapter 6, Image neighborhood filtering Section 4.3, Spatial Filtering, pp. 189-200 Image Filtering in the Frequency Domain Image Transformations and Filters |
| Filters, Convolution | Note from Lazikas o Pontios about convolution filters.
Dr. John Russ’ UseNet Post to comp.graphics.algorithms (19 July 2000): Convolution Convolution, pp. 67-73 Section 6.3, Linear filtering using convolution, High Performance Computer Imaging. Chris Russ’ UseNet Post about Fast Convolution Algorithms |
| Filters, Derivatives | pp. 250-254, The Image Processing Handbook
Filters, Sobel and Kirsch First Order Derivatives Operators, pp. 86-88 |
| Filters, Laplacian | pp. 242-250, The Image Processing Handbook
Gaussian Filter LoG (Laplacian of Gaussian): Chris Russ’ UseNet Post about LoG operators of various sizes |
| Filters, Median and Rank |
Optimal median smoothing, Applied Statistics, 44(2): 258-264, W. Haerdle, W. and M. Steiger, 1995. Haerdle and Steiger’s approach is O(log p) per pixel, where p is the width of the kernel. ftp://amadeus.wiwi.hu-berlin.de/pub/papers/sfb373/sfb1994/dpsfb940015.ps.Z Median Filtering, pp. 95-107 (includes color median filtering, p. 103) Fast Median Search: an ANSI C implementation Median Filter Adaptive Center Weighted Median Filter Filtre Médian (3×3, 5×5) Diagram of optimal way to compute median value from 3×3 array in hardware. Use the same logic in software. www.xilinx.com/xcell/xl23/xl23_16.pdf Median filters are useful tools in digital signal processing. Wesley examines their use for removing impulsive signal noise while maintaining signal trends. Additional resources include aa1099.txt(listings). Spyros’ UseNet Post about Huang’s Algorithm Rank operations, pp. 268-277 Section 6.4, Nonlinear filtering I: the median filter and its variations |
| Filters, Morphological | Section 6.5, High Performance Computer Imaging Nonlinear filtering II: morphological filters |
| Filters, Sharpening | p. 177, High Performance Computer Imaging. Includes discussion of unsharp masking.
3. Differentiation, Sharpening, Enhancement, Caricatures and Shape Morphing Sharpening, pp. 77-79 |
| Filters, Smoothing | pp. 176-177, High Performance Computer Imaging
Gaussian Smoothing |
| Filters, Unsharp Mask | Chris Russ’ UseNet Post about implementing unsharp mask Chris Russ’ UseNet Post about two common uses for unsharp mask Unsharp masking is a photographic technique that increases the sharpness of photographic images. Tim presents an algorithm that implements this concept. Additional resources include aa1199.zip (source code). |
| Fingerprints | See Recognition, Fingerprints |
| Fluorescence Imagnig | Fluorescence Imaging Applications Guide Fluorescence Imaging Principles and Methods |
| Focus | Chris Russ’ UseNet Post about AutoFocus methods |
| Fractal analysis | pp. 282-288, The Image Processing Handbook |
| Gray Scales | Perceptually Optimized Grayscales www.fho-emden.de/~hoffmann/optigray06102001.pdf |
| Gamma correction | efg’s Color Reference Library |
| Gray Scale Images | Fast Gaussian blurring; Operations on gray scale images; Generalized order statistic filters; Contour construction for 2D image. (Requires Magic Software) www.magic-software.com/im_gray.htm |
| Halftoning | A Review of Halftoning Techniques
Digital Halftoning, Chapter 6 Gernot Hoffmann’s “Dithering + Halftoning” |
| Histogram equalization | Use of computer graphic simulation to explain color histogram structure www.graphics.cornell.edu/pubs/1997/PLG97.html pp. 233- 241, The Image Processing Handbook |
| Histograms | Display/Print Histograms (R, G, B, H, S, V) efg’s Show Image efg’s HistoStretchGrays Lab Report Histogram-base Operations: Contrast stretching, equalization Histogram Specification, pp. 49-54 Histogram-based operations, pp. 143-150 Three-way histograms (RGB, YUV, HSI) Section 4.2.2, Histogram Processing, pp. 171-185 |
| Hough Transform | Hough Transform: Journal and Conference Papers http://ipml.ee.duth.gr/~papamark/Hough.html 8. Detection of Structure in Noisy Pictures and Dot Patterns On the Efficient Sampling Interval of the Parameter in Hough Transform Hough Transforms XHoughTool Kim Madsen’s UseNet Post about Hough Transform |
| Image Analogies | http://mrl.nyu.edu/projects/image-analogies/index.html |
| Image Query | Fast Multiresolution Image Querying www.cs.washington.edu/research/projects/grail2/www/projects/query Shape Queries Using Image Databases Also see book Wavelets for Computer Graphics |
| Interpolation and Extrapolation | See Resampling
Michel Chabroux’s UseNet Post explaining bilinear interpolation |
| Jitter | Infrared jitter imaging data reduction algorithms www.eso.org/projects/dfs/papers/jitter99 |
| Lens Transformation | http://thorkildsen.no/faqsys/docs/lens.txt
Nonlinear Lens Distortion Computer Generated Angular Fisheye Projections Eric Rudd’s UseNet Post about fisheye lens simulation |
| Lighting | efg’s Color Reference Library |
| Masks | Chapter 7, Processing Binary Images, pp. 431-508 The Image Processing Handbook |
| Measurements | Chapter 8, Image Measurements, pp. 509-574 The Image Processing Handbook Chapter 16, Size and Shape, pp. 485-508 |
| Metamorphisis | Feature-Based Image Metamorphosis www.hammerhead.com/thad/morph.html |
| Metrology | Metrology based on Computer Vision www.cranfield.ac.uk/sme/amac/research/metrology/metrology.html |
| Moiré Methods | “Moiré Methods Make Shape Recognition Easier” Vision Systems Design, March 1997, pp. 32-37 Modelization of the Moiré Phenomenon Moiré Effects With Overlayed Line Screens |
| Moments of Inertia | www.cm.cf.ac.uk/Dave/AI2/node194.html
On the Calculation of Arbitrary Moments of Polygons |
| Morphology | Understanding mathematical morphology Vision Systems Design, May 1999 Understanding more mathematical morphology Morphological Image Analysis: Principles and Applications (June 1999). Author’s page The Morphology Digest is intended as a forum between workers in the field of Mathematical Morphology and related fields (stochastic geometry, random set theory, image algebra, etc.). Mathematical Morphology and Image Interpolation SDC Morphology Toolbox for MATLAB: includes fast queue-based algorithms for distance transform, watershed, reconstruction, labeling, area-opening, etc. |
| Mosaicing | Rho Ophiucus Mosiac Processing Example www.jps.net/jrfcomet/tech/rho.htm An Introduction to Image Mosaicing Image Registration and Mosaicking Automatic Panoramic Image Merging Mosaicing with Super Resolution |
| Motion | Image Sequence Segmentation www.uwm.edu/~gjb/thesis.html Estimation of Visual Motion in Image Sequences Chris Russ’ UseNet Post with suggestion on how to detect motion by image difference Section 5.4.2, Removal of Blur Caused by Uniform Linear Motion, pp. 272-278 Motion Introduction to Active Contours and Visual Dynamics Motion and Time Sequence Analysis Thomas Kragh’s UseNet Post about Motion Blur Chapter 13, Orientation and Velocity, 415-440 |
| Neural Networks | Neural Network as a Tool for Feature Selection www.prettyview.com/ann/nnfs.shtml |
| Noise Removal | Noise Removal from Images www.math.berkeley.edu/~sethian/Movies/Movienoiseremoval.html The SUSAN algorithms cover image noise filtering, edge finding and corner finding. Median filters are useful tools in digital signal processing. Wesley examines their use for removing impulsive signal noise while maintaining signal trends. Additional resources include aa1099.txt(listings). Also see Median Filters |
| Nyquist Limit | Using a Nyquist Chart to Evaluate Digital Camera Systems Part 1. www.photobit.com/Technology/White_Papers/Using_a_Nyquist_Chart_1/using_a_nyquist_chart_1.htm Part 2. |
| Optimization | Using MMX Technology to Speed Up Machine Vision Algorithms Part 1. www.imaging.com/techinfo/tutorials/00000009/tutorial.html Part 2. www.imaging.com/techinfo/tutorials/00000015/tutorial.html |
| Panoramic Images | Helmut Dersch’s “Panorama Tools: Documentation, Info and More Uses” http://www.fh-furtwangen.de/~dersch (Be wary of IPIX, however.) |
| Perimeter | efg’s E-mail to Engineering Student at kmutt about how to computer perimeter of an object |
| Photogrammetry | See General Info page |
| Point Operations | Monadic image operations: add constant, subtract constant, multiply constant, divide into constant, divide by constant, or constant, and constant, xor constant
Diadic image operations: add, subtract, multiply, divide, min,max, or, and, xor |
| Radon Transform | http://eivind.imm.dtu.dk/staff/ptoft/Radon/Radon.html |
| Recognition | Recognizing Flexible Objects www.cs.cornell.edu/vision/pff/boom99 Point Pattern Matching Chris Russ’ UseNet Post about fixing broken lines in image recognition Pattern Classification and Scene Analysis (book) “Moiré Methods Make Shape Recognition Easier” Chapter 9, Recognition and Interpretation, pp. 571-661 See also Skeletonization |
| Recognition, Faces | The Face Detection Home Page www.facedetection.com Face Recognition Home Page Multi-Modal System for Locating Heads and Faces Locating Faces and Facial Parts Bayesian Modeling of Facial Similarity Computer Vision Face Tracking For Use in a Perceptual User Interface The Biometric Consortium, Research and Databases Face detection, recognition and analysis Intelligent Biometric Techniques in Fingerprint and Face Recognition |
| Recognition, Fingerprints | Biometrics http://dmoz.org/Computers/Security/Biometrics The Biometric Consortium, Reseat and Databases Fingerprint Enhancement, www.kttech.com/fingerpr.html FBI Fingerprint Image Compression Standard FAQ about FBI’s Wavelet/Scalar Quantization Specification for compression of digitized gray-scale fingerprint images. Intelligent Biometric Techniques in Fingerprint and Face Recognition US UK |
| Recognition, Handwriting | The Biometric Consortium, Reseat and Databases Face, Fingerprints, Handwriting, Voice www.biometrics.org/html/research.html Fingerprints and handwriting NIST Form-Based Handprint Recognition System |
| Recognition, Iris | Iris Recognition Homepage www.iris-recognition.org |
| Recognition, License Plates | Vehicle Number Plate Recognition Home Page Universidade de Trás-os-Montes e Alto Douro www.utad.pt/numberplate A Neural Network Based Artificial Vision System for Licence Plate Recognition |
| Recognition, Optical Character (OCR) | Character Recognition http://web.mit.edu/stanrost/www/cs585p1/p1.html Optical Character Recognition: Journal and Conference Papers Character Recognition OCR/ICR Documents Character Recognition by Feature Point Extraction Document Understanding and Character Recognition WWW Server Chapter 8, Optical Character Recognition, pp. 275-304 Geometry in Action |
| Recognition, Pattern | Pattern Recognition Links http://cgm.cs.mcgill.ca/~godfried/teaching/pr-web.html Understanding Pattern Recognition, Visions Systems Design, July 1999. Pattern Recognition Resources, www.dcs.ex.ac.uk/paa/resources.htm Pattern Recognition Information, www.ph.tn.tudelft.nl/PRInfo.html Statistical Pattern Recognition & Artificial Neural Network Library Optimizing Vision Applications: Which is Better, Blob-Centroid or Grayscale Search? |
| “Red Eye” | See efg’s Color and Computers page |
| Representation | Chapter 8, Representation and Description, pp. 483-569 Digital Image Processing |
| Resampling | Advanced Image Processing: Image Interpolation and Filtering www.engineering.uiowa.edu/~gec/248_s00_students/blake_carlson/hw2 Interpolation for Scaling, Rotation, Perspective and Morphing Interpolation (Nearest Neighbor, Bilinear, Cubic Convolution, B-Spline), pp. 110-123 Digital Image Processing: Principles and Applications, pp. 117-122 Image Processing By Interpolation and Extrapolation Efficient Image Magnification by Bicubic Spline Interploation Mathematical Morphology and Image Interpolation Section 8.3.2, “Interpolation,” in Paul Heckbert’s “zoom” program Non-Linear Magnification Home Page Note from Lazikas o Pontios abut Resampling to zoom. Testing Interpolator Quality |
| Restoration, Reconstruction | Electronic Imaging, a Tool for the Reconstruction of Faded Color Photographs http://www.foto.unibas.ch/research/paper1/restor.html Image Restoration “Novel Blind Deconvolution Techniques Restore Blurred Images” Chapter 3, Correcting Image Defects, pp. 161-226 Chapter 5, Image Restoration, pp. 253-306 Chapter 6, Image Restoration, pp. 220-249 Chapter 9, Restoration and Reconstruction, pp. 287-306 |
| Rotation | Turn, Turn, Turn: Using the Graphics Class to Rotate Images http://msdn.microsoft.com/library/periodic/period99/turn.htm HOWTO: Display a Bitmap into a Rotated or Non-rectangular Area “High Accuracy Rotation of Images,” in Computer Vision, Graphics and Image Processing, Vol. 54, No. 4, July 1992, pp. 340-344. One-pass and multipass rotation, Section 8.5 2-pass and 3-pass rotations comp.graphics.algorithms FAQ, Section 3.01, www.exaflop.org/docs/cgafaq In Windows NT the plgblt API call can be used for bitmap rotation if the RC_BITBLT is supported by a device. See efg’s RotateScanline, RotatePixels and FlipReverseRotate Lab Reports. |
| Scaling | Bitmap Scaling www.ddj.com/ftp/1997/1997.04/asc.zip/2ddda.asc Section 8.4, High Performance Computer Imaging, Image Scaling |
| Segmentation | Digital Image Processing: Principles and Applications, pp. 124-152
Image Segmentation and Mathematical Morphology Image Sequence Segmentation Many image-analysis tasks must first separate the image into clearly defined regions. Lee’s algorithm performs such a separation and presents the results in a fashion amenable to further study. Additional resources include aa798.txt (listings) and aa798.zip (source code). July 1998, Dr. Dobb’s Journal. www.ddj.com/articles/1998/9807/9807toc.htm Skin Cancer Segmentation program Efficiently Computing a Good Segmentation Understanding Image Segmentation Basics Understanding Region-Based Segmentation Understanding Oversegmentation and Region Merging Understanding Undersegmentation and Region Splitting Understanding Edge- and Line-Based Segmentation Understanding other edge- and line-based segmentation techniques Segmentation Color Image Segmentation (with C++ code) Unsupervised Segmentation Chapter 6, Segmentation and Thresholding, pp. 371-430 Chapter 7, Image Segmentation, pp. 413-482 Chapter 15, Segmentation, pp. 474-484 Also see Segmentation on efg’s Color Reference Library page |
| Shape from Shading | A method for determining the shape of a surface from its image www.psrw.com/image/ShapeFromShading/shape.html |
| Sharpness | see links under MTF |
| Skeletonization | Digital Image Processing: Principles and Applications, pp. 137-139
The Scale Space Skeletonization Page Hilditch’s Algorithm for Skeletonization Skeletonization in 2D, 3D and 4D images Comparison of Skeletonization Methods |
| Skew | Skew Correction http://ipml.ee.duth.gr/~papamark/free_software2.htm |
| Snakes | Gradient Vector Flow (GVF) snake. Active contours — or snakes — are computer-generated curves that move within images to find object boundaries. http://iacl.ece.jhu.edu/projects/gvf GVF snake for *nix boxes source code Snakes Active Snakes Active Contours (Snakes) Active contour models of shape or “snakes” Snakes: Active Contour Models GSNAKE API |
| Special Effects | Beyond Photography — The Digital Darkroom (Out of Print, 1995) Publisher Web Site: http://www.phptr.com/ptrbooks/ptr_0130744107.html |
| Spectroscopy | USGS Imaging spectroscopy analysis: identify and map materials through spectroscopic remote sensing, on the earth and throughout the solar system. http://speclab.cr.usgs.gov About Imaging Spectroscopy, http://speclab.cr.usgs.gov/aboutimsp.html Multispectral Scanner Landsat Data |
| Steganography | The information hiding homepage – digital watermarking & steganography www.cl.cam.ac.uk/%7Efapp2/steganography Steganography Steganography & Digital Watermarking Steganography/Watermarking Information Stenography and Digital Watermarks Also see watermarking |
| Stereoscopic Vision | Stereo pair displays of surface range images http://members.AOL.com/DrJohnRuss/stereo.pdf Single-Image Stereograms, July 1995, Dr. Dobb’s Journal. Stereoscopic, or true 3-D, images take into account depth information that’s lost when conventional 3-D images are projected onto a PC’s 2-D screen. In addition to discussing hardware and software stereoscopic requirements, our authors present and implement algorithms for generating left- and right-eye views fundamental to stereoscopic viewing. April 1994, Dr. Dobb’s Journal. www.ddj.com/articles/1993/9304/9304toc.htm Stereoscopic Vision and Perspective Projection Stereo Vision |
| Texture | Fast Marble Texture Algorithm www.cubic.org/~submissive/sourcerer/marble.htm pp. 278-282, The Image Processing Handbook Chapter 4, Texture, pp 150-175 Chapter 14, Scale and Texture, pp. 441-469 |
| Thermal Imaging | “Thermal Imaging Is Gaining Acceptance as a Diagnostic Tool” Biophotonics International, Nov/Dec 1998, pp. 48-53 |
| Thresholding | Chapter 6, Segmentation and Thresholding, pp. 371-430 The Image Processing Handbook Section 7.3, Thresholding, pp. 443-457 |
| Transformation | Image Transformations (Chapter 7) Frequency Domain; Discrete Fourier Transform; FFT; Discrete Cosine Transform Simplified Approach to Image Processing |
| Transformation, Affine | Affine transformation software http://bigwww.epfl.ch/thevenaz/affine/index.html Affine texture mapping is fundamental to many forms of 3D rendering, including light interpolation and other sampling type operations. Additional resources include tmapper.txt (listings) and tmapsrc.zip(source code). Dr. Dobb’s Journal, July 1998. www.ddj.com/articles/1998/9807/9807toc.htm Section 8.6, High Performance Computer Imaging, Affine transformation Curvature Scale Space image under affine transforms |
| Transformation, Special effects | Section 8.8, High Performance Computer Imaging, Special-effects filters. Shows radial transformation Spatial Transformations (affine, perspective, bilinear, meshwarp) |
| Transparency | Sean Dockery’s UseNet Post about Transparency including links to Microsoft Technical Reports |
| Triangle Intersection | Triangle Intersection Tests Dr. Dobb’s Journal, August 2000 |
| Unsharp Masking | “Real” Digital Unsharp Masking: A Digital Equivalent to a Film Technique www.astropix.com/HTML/J_DIGIT/USM.HTM |
| Warping | Digital Image Processing: Principles and Applications, pp. 115-117
Fields-Based Warping, pp. 234-243 |
| Watermarking | nformation Hiding Techniques for Steganography and Digital Watermarking by Fabien Petitcolas and Stefan Katzenbeisser US UK Author’s Web Site The information hiding homepage – digital watermarking & steganography Digital Watermarking World Invisible Watermarking: Protecting Digital Pictures References on Multimedia Watermarking and Data Hiding Research & Technology Watermarking of Video and Multimedia Data Digital watermarking: perfecting the art of security Digital Watermarking Digital Watermarking: a solution to Electronic Copyright Management Systems Requirements Watermarking of Digital Images Also see Steganography |
| Watershed Transformation | Watershet Edge Detection, pp. 148-153 Digital Image Processing: Principles and Applications Several papers on Watershed algorithms SDC Morphology Toolbox for MATLAB: includes fast queue-based algorithms for distance transform, watershed, reconstruction, labeling, area-opening, etc. www.mmorph.com Watershed Transform Image segmentation problems in mathematical morphology |
| Zoom | See ResamplingImage Registration |
| Automated Image Registration | http://bishopw.loni.ucla.edu/AIR5 |
| Automatic Panoramic Image Merging | www.sgi.com/grafica/merge/index.html |
| Automatic Registration of SAR Images and Digitized Maps | www.engr.mun.ca/~charlesr/summary.html |
| Bibliography | Michael Jacobs’ UseNet Post with many references to journal articles |
| CISG Registration Toolkit | www-ipg.umds.ac.uk/cisg/vtk-software |
| Cross-Correlation | Fast Normalized Cross-Correlation www.idiom.com/~zilla/Papers/nvisionInterface/nip.html |
| Elastic Image Registration | www.loni.ucla.edu/~thompson/ElasChpt.html
Elastic Imaging Registration and Pathology Detection |
| FFT | Reddy, B. Srinivasa and B. N. Chatterji, “An FFT-Based Technique for Translation, Rotation, and Scale-Invariant Image Registration,” IEEE Trans. Image Processing vol. 5, no. 8 (1996 August) pp. 1266-1271. |
| FLIRT | FLIRT is software for linear image registration, which is part of FSL www.fmrib.ox.ac.uk/fsl |
| Image Matching and Registration | www.dra.hmg.gb/cis5/ipi13b.html |
| Image Matching by Maximisation of Mutual Information | www.robots.ox.ac.uk:5000/~seb/matching/mutual_info.html |
| Image Registration | Special Issue of Pattern Recognition on Image Registration www.cs.wright.edu/people/faculty/agoshtas/ImgReg.html |
| Image Registration and Mosaicking | www.prettyview.com/mtch/mtch.shtml |
| Image Registration Technology | KT-Tech, Inc. www.kttech.com/top/reg.htm |
| Matching Algorithms for Medical Image Processing | http://mbi.dkfz-heidelberg.de/mbi/research/matching.html |
| Medical Image Registration | New Book (June 2001) US UK DE FR |
| Medical Image Registration using Geometric Hashing | www.computer.org/cse/cs1997/c4029abs.htm |
| Multimodality Medical Image Registration | www.seas.gwu.edu/seas/institutes/medimage/registration |
| Raw Image Registration | NewSips System www.vilspa.esa.es/iue/IUEFA/manual/chap00/node26.html Cross-Corr |
| Retrospective Registration Evaluation Project | www.vuse.vanderbilt.edu/~jayw |
| Role of Image Registration in Brain Mapping | www.loni.ucla.edu/~thompson/IVCJ_99.html www.loni.ucla.edu/~thompson/PDF/IVCJ_99.pdf |
| Survey of image registration techniques | Abstract from ACM Computing Surveys, Vol 24., No. 4, Dec 92, pp. 325-376 |
| Survey of Medical Image Registration | J.B.A. Maintz, Medical Image Analysis, 2(1):1-36, 1998. www.cs.uu.nl/people/twan/personal/media97.pdf An overview of medical image registration methods. In Symposium of the Belgian hospital physicists association (SBPH/BVZF), volume 12, pages V:1-22, 1996/1997. Author’s Bibliographical Information: www.cs.uu.nl/people/twan/personal/list.html |
| 3D Image Registration of CT Angiography | www.ee.princeton.edu/~mingy/cta |
| 3D Image Registration for Sculptors | www.sculptor.org/register.htm |
Mathematical Techniques
Also see Fourier Analysis and Wavelets Sections of efg’s Mathematics Page
| DCTs | Implementing Fast DCTs (Discrete Cosine Transforms) Dr. Dobb’s Journal, March 1999, pp. 115-119 |
| Fast Hartley Transform | Hartley Transform www.treasure-troves.com/math/HartleyTransform.html Note: According to a letter to the editor in the July 1999 “Embedded Systems Programming” (p. 7) the Fast Hartley Transform is covered under U.S. Patent Number 4,646,256. Use of this algorithm for noncommercial research must be negotiated with the Office of Technology Licensing at Stanford University. |
| Geometry | Vision Geometry and Mathematics www.dai.ed.ac.uk/CVonline/geom.htm Section 2.5, Imaging Geometry, pp. 51-71 Chapter 8, Geometry, pp. 263-286 Chapter 8, Image geometric operations |
| Image Quality | IQM Approach: Obtain Quality from Image Power Spectrum www.mitre.org/technology/mtf/poster.pdf Objective Image Quality Measure Derived from Digital Image Power Spectra Also see Modulation Transfer Function below |
| Image Transforms | Chapter 3, pp. 81-159 Fourier Transform (3.1), Walsh Transform (3.5.1), Hadamard Transform (3.5.2), Discrete Cosine Transform (3.5.3), Haar Transform (3.5.4), Slant Transform (3.5.5), Hotelling Transform (3.6) Digital Image Processing, 2nd edition |
| Modulation Transfer Function | Random Test Patterns To Evaluate MTF www.precisionopticalimaging.com/notes/notes.asp Understanding image sharpness part 1: resolution and MTF curves in film and lenses. www.normankoren.com/Tutorials/MTF.html Understanding image sharpness part 2: resolution and MTF curves in scanners and sharpening Understanding MTF Testing How to interpret MTF Graphs Use of Sinusoidal Test Patterns for MTF Evaluation Image Quality Evaluation: Modulation Transfer Function What is a MTF Curve? |
| Moments | Section 8.3.4, Moments, pp. 514-518 Digital Image Processing |
| Matrices | Matrix Operations for Image Processing www.sgi.com/grafica/matrix/index.html |
| Point Spread Functions | The point-spread function (PSF) model of blurring http://extreme.indiana.edu/~tveldhui/papers/MAScThesis/node10.html Point Spread Function of Imaging System (diagram) Point spread function of the human eye obtained by a dual double-pass method Point and Line Spread Functions ACIS/HRMA Point Spread Function |
| Statistics | Statistics and Image Processing www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-Statisti.html |
| White Balance | White Balance Patents www.frontiernet.net/~shyam/whitebalance.htm |
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