The Colour Image Processing HandbookStephen J. Sangwine, Robin E.N. Horne Springer Science & Business Media, 30 avr. 1998 - 440 pages 1. The present state and the future of colour image processing; 2. Colour vison; 2.1 What is colous?; 2.2 The visual pathway; 2.3 Light absorption and trichromacy; 2.4 Colour appearance and opponet processes; 2.5 Other phenomena; 2.6 The uses of colour; 3. Colour science; 3.1 Introduction; 3.2 The CIE system; 3.3 Colour measurement instruments; 3.4 Uniform colour spaces and colour difference formulas; 3.5 Colour appearance modelling; 4. Colour spaces; 4.1 Basic RGB colour space; 4.2 XYZ colour spae; 4.3 Television colour spaces; 4.4 Opponent colour space; 4.5 Ohta I1I2I3 colour space; 4.6 IHS and related percentual colour spaces; 4.7 Perceptually unifor colour spaces; 4.8 Munsell colour system; 4.9 Kodak Photo YCC colour space; 4.10 Summary of colour space properties. 5. Colour video systems and signals; 5.1 Video communication; 5.2 Colour reproduction; 5.3 Encoded-colour systems; 6. Image sources; 6.1 Overview of sources for image processing; 6.2 Cameras; 7. Practical system considerations; 7.1 Image acquisition technique; 7.2 Image storage; 7.3 Colorimetric calibration of acquisition hardware; 8. Noise removal and contrast enhancement; 8.1 Noise removal; 8.2 Contrast enhancement; 9. Segmentation and edge detection; 9.1 Pixel-based segmentation; 9.2 Region-based segmentation; 9.3 Edge detection and boundary tracking; 9.4 Segmentation adn edge detection quality metrics; 10 Vector filtering; 10.1 the vector median filter; 10.2 Vector direcitonal filters; 10.3 Adaptive vector processing filters; 10.4 Application to colour images; 11. Morphological operations; 11.1 Mathematical morphology; Colour morphology; 11.3 Multiscale image analysis; 11.4 Image enhancement; 12. Frequenci domain methods; 12.1 Review of the 2D discrete Fourier transform; 12.2 Complex chromaticity; 12.3 The quaternion Fourier transform; 12.4 Disicussion; 13. Compression; 13.1 Image and video compression; 13.2 Component-wise still image compression; 13.3 Exploitation of mutual colour component dependencies; 13.4 Colour video comression; 14. Colour management for the textile industry; 14.1 Overviwe of colour flow in the textile industry; 14.2 Colour management systems; 14.3 CRT characterization; 14.4 WYSIWYG colour management; 14.5 Colour notation; 14.6 Colour quality control; 14.7 The colour talk system; 15. Colour management for the graphic arts; 15.1 Overview of the graphic arts environment; 15.2 Colour management systems overview; 15.3 Characterization and calibration of system components; 15.4 Gamut mapping; 15.5 Current colour management systems; 16 Medical imaging case study; 16.1 Wound metrics: the background and motiviation; 16.2 Principle of structured ligh; 16.3 Implementatin of the status of healing; 16.4 Assessment of the status of healing; 16.5 Automatic segmentation of the wound; 16.6 Visualization and storage of data; 17. Industrial colour inspection case studies; 17.1 Inspection of printed card; 17.2 Inspection of fast-moving beverage cans; References; Index. |
Table des matières
LXI | 230 |
LXII | 234 |
LXIII | 239 |
LXIV | 241 |
LXV | 250 |
LXVI | 271 |
LXVII | 296 |
LXVIII | 307 |
LXIX | 308 |
LXX | 312 |
LXXI | 315 |
LXXII | 318 |
LXXIII | 325 |
LXXIV | 327 |
LXXV | 331 |
LXXVI | 332 |
LXXVII | 333 |
LXXVIII | 334 |
LXXIX | 345 |
LXXX | 353 |
LXXXI | 357 |
LXXXIII | 358 |
LXXXIV | 360 |
LXXXV | 364 |
LXXXVI | 368 |
LXXXVII | 371 |
LXXXVIII | 374 |
LXXXIX | 376 |
XCI | 377 |
XCII | 379 |
XCIII | 384 |
XCIV | 424 |
Autres éditions - Tout afficher
The Colour Image Processing Handbook Stephen J. Sangwine,Robin E.N. Horne Aucun aperçu disponible - 2012 |
The Colour Image Processing Handbook Stephen J. Sangwine,Robin E.N. Horne Aucun aperçu disponible - 2011 |
Expressions et termes fréquents
adaptive algorithm appearance applications approach blue calculated called camera channel Chapter chromatic CIELAB coding colour image colour space combination complex components composite video compression cone Conference corresponding defined described determined developed device directional discussed display distance edge effect equation error example field filter frequency function gamut given green illumination image processing important input intensity light linear luminance mapping matching mean measure method noise object obtained operations original output palette perform pixel Plate position possible presented problem Proceedings processing produce proposed quantization range ratio reference reflectance region represent representation sample scan segmentation separate shown shows signal similar smoothing spatial spectral standard Step surface Table techniques tion transform usually values vector viewing vision visual wound
Fréquemment cités
Page 57 - ... saturation — attribute of a visual sensation according to which an area appears to exhibit more or less chromatic color, judged in proportion to its lightness or brightness.
Page 195 - The so-called DirectionalDistance Filter (DDF) retains the structure of the BVDF but utilizes a new distance criterion to order the vectors inside the processing window. Based on the observation that the BVDF and the VMF differ only in the quantity that is minimized, a new distance criterion was utilized by the designers of DDF in hopes to derive a filter which combines the properties of both these filters.
Page 57 - Lightness: the brightness of an area judged relative to the brightness of a similarly illuminated area that appears to be white...
Page 194 - Generalized Vector directional Filter (GVDF) generalizes BVDF in the sense that its output is a superset of the single BVDF output. Instead of a single output, the GVDF outputs the set of vectors whose angle from all other vectors is small as opposed to the BVDF which outputs the vector whose angle from all the other vectors is minimum. Thus...
Page 194 - The output of the BVDF is that vector from the input set, which minimizes the sum of the angles with the other vectors. In other words, the BVDF chooses the vector most centrally located without considering the magnitudes of the input vectors. To improve the efficiency of the directional filters, another method called Directional-Distance Filter (DDF) was proposed in [3]. This filter retains the structure of the BVDF but utilizes a new distance criterion to order the vectors inside the processing...
Page 196 - This filter operates on the direction and the magnitude of the color vectors independently and then combines them to produce a unique final output. This hybrid filter, which can be viewed as a nonlinear combination of the VMF and BVDF filters, produces an output according to the following rule...
Page 62 - H 0 100 200 300 h 20.14 90.00 164.25 237.53 e 0.8 0.7 1.0 1.2 e\ and h\ are the values of e and h, respectively, for the unique hue having the nearest lower value of h; and e2 and h2 are these values for the unique hue having the nearest higher value of h.
Page 188 - It is widely accepted that colour conveys information about the objects in a scene and that this information can be used to further refine the performance of an imaging system.
Page 62 - „ 100(AA,)/e, (e2-e\) h2-h\ where H\ is 0, 100, 200, or 300, according to whether red, yellow, green, or blue, respectively, is the hue having the nearest lower value of h.
Page 206 - In summary, our design is simple, does not increase the numerical complexity of the multichannel algorithm and delivers excellent results for complicated multichannel signals, such as real colour images.
