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E-raamat: Art and Science of HDR Imaging

(Consultant, McCann Imaging, USA), (Università degli Studi di Milano, Italy)
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Rendering High Dynamic Range (HDR) scenes on media with limited dynamic range began in the Renaissance whereby painters, then photographers, learned to use low-range spatial techniques to synthesize appearances, rather than to reproduce accurately the light from scenes. The Art and Science of HDR Imaging presents a unique scientific HDR approach derived from artists’ understanding of painting, emphasizing spatial information in electronic imaging.

Human visual appearance and reproduction rendition of the HDR world requires spatial-image processing to overcome the veiling glare limits of optical imaging, in eyes and in cameras. Illustrated in full colour throughout, including examples of fine-art paintings, HDR photography, and multiple exposure scenes; this book uses techniques to study the HDR properties of entire scenes, and measures the range of light of scenes and the range that cameras capture. It describes how electronic image processing has been used to render HDR scenes since 1967, and examines the great variety of HDR algorithms used today. Showing how spatial processes can mimic vision, and render scenes as artists do, the book also:

  • Gives the history of HDR from artists' spatial techniques to scientific image processing
  • Measures and describes the limits of HDR scenes, HDR camera images, and the range of HDR appearances
  • Offers a unique review of the entire family of Retinex image processing algorithms
  • Describes the considerable overlap of HDR and Color Constancy: two sides of the same coin
  • Explains the advantages of algorithms that replicate human vision in the processing of HDR scenes
  • Provides extensive data to test algorithms and models of vision on an accompanying website
    www.wiley.com/go/mccannhdr

Arvustused

Overall, this book provides an excellent overview of the history of imaging, HDR imaging algorithms, and the abilities of the human visual system. The book is a great achievement for the authors, and it will be well appreciated by anyone who enjoys learning about a field from the key players. Most importantly, it will encourage the reader to think about how visual processing works, and how that process can serve as a model for imaging systems for HDR images.  (Journal of Electronic Imaging, 1 September 2012)

About the Authors xix
Preface xxi
Series Preface xxiii
Acknowledgements xxv
Section A HISTORY OF HDR IMAGING
1(88)
1 HDR Imaging
3(10)
1.1 Topics
3(1)
1.2 Introduction
3(1)
1.3 Replicas and Reproductions
4(1)
1.4 A Choice of Metaphors for HDR Reproduction
5(2)
1.6.1 Pixel-based Reproduction
5(1)
1.6.2 Spatial Reproduction
6(1)
1.5 Reproduction of Scene Dynamic Range
7(1)
1.6 HDR Disciplines
8(2)
1.6.1 Interactions of Light and Matter
8(1)
1.6.2 Light Sensors
8(1)
1.6.3 Image Processing
8(2)
1.6.4 Image Rendition
10(1)
1.7 Outline of the Text
10(1)
1.7.1 Section A -- History of HDR Imaging
10(1)
1.7.2 Section B -- Measured Dynamic Ranges
10(1)
1.7.3 Section C -- Separating Glare and Contrast
10(1)
1.7.4 Section D -- Scene Content Controls Appearances
11(1)
1.7.5 Section E -- Color HDR
11(1)
1.7.6 Section F -- HDR Image Processing
11(1)
1.8 Summary
11(1)
1.9 References
12(1)
2 HDR Tools and Definitions
13(14)
2.1 Topics
13(1)
2.2 Introduction
13(1)
2.3 Pixels
14(1)
2.4 Dynamic Ranges
14(3)
2.4.1 Dynamic Range of Light in Scenes
14(1)
2.4.2 Dynamic Range of Vision
15(2)
2.5 Measuring Light
17(1)
2.5.1 Radiometry -- Measuring Electromagnetic Radiation
17(1)
2.5.2 Photometry -- Measuring Visible Light
17(1)
2.6 Measuring Color Spaces
18(3)
2.6.1 Color Matching Functions
19(1)
2.6.2 Uniform Color Spaces
19(2)
2.6.3 Early Pixel-based Color Matches Followed by Neural Spatial Interactions
21(1)
2.7 Image Reproduction
21(3)
2.7.1 Color-Forming Technologies
22(1)
2.7.2 Spatial Additive Color in Flat-Panel Displays
23(1)
2.7.3 Tone Scale Control of the Interior Color Space
23(1)
2.7.4 Colorimetric Reproductions
24(1)
2.8 Contrast
24(1)
2.9 Digital Imaging
25(1)
2.10 Summary
25(1)
2.11 References
26(1)
3 HDR in Natural Scenes
27(6)
3.1 Topics
27(1)
3.2 Appearance in HDR and Color Constancy
27(3)
3.3 Summary
30(1)
3.4 References
31(2)
4 HDR in Painting
33(12)
4.1 Topics
33(1)
4.2 Introduction
33(1)
4.3 Ancient Painting
33(2)
4.4 Perspective
35(2)
4.4.1 Perspective in the Renaissance
36(1)
4.5 Chiaroscuro
37(1)
4.6 Gerritt van Honthorst (Gherardo delle Notti)
37(3)
4.7 Rembrandt van Vijn
40(1)
4.8 John Constable
40(1)
4.9 John Martin
40(1)
4.10 Impressionism
41(2)
4.11 Photorealism
43(1)
4.12 Summary
43(1)
4.13 References
44(1)
5 HDR in Film Photography
45(14)
5.1 Topics
45(1)
5.2 Introduction
45(1)
5.3 Multiple Exposures in the 1850s
46(1)
5.3.1 Edouard Baldus
46(1)
5.4 HP Robinson
47(1)
5.5 Hurter and Driffield-Scientific Calibration of AgX Film Sensitivity
48(2)
5.6 Sheppard and Mees
50(1)
5.7 19th Century -- Professional Amateur Photography
50(1)
5.8 20th Century -- Corporate Photography
50(1)
5.9 20th Century Control of Dynamic Range
51(5)
5.9.1 The Tone Scale Curve
51(1)
5.9.2 The Physics Behind the Tone Scale Curve
52(1)
5.9.3 Jones and Condit -- Range of Light in Scenes
52(1)
5.9.4 Color Film
53(1)
5.9.5 LA Jones
53(1)
5.9.6 Color Measurement vs. Color Photography
54(2)
5.9.7 HDR Pseudocolor Measurement -- Wyckoff
56(1)
5.10 Other Silver-Halide Stories
56(1)
5.11 Summary
56(1)
5.12 References
57(2)
6 The Ansel Adams Zone System
59(10)
6.1 Topics
59(1)
6.2 Introduction
59(1)
6.3 Compressing the HDR World into the LDR Print
59(1)
6.4 Visualization
60(1)
6.5 Scene Capture
61(4)
6.5.1 Assigning Scene Luminances to Zones in the Print
61(1)
6.5.2 Zone System: Interplay of Exposure and Development
61(2)
6.5.3 Compressing the HDR Scene into the LDR Print -- Spatial Image Processing
63(2)
6.6 "Performing the Score"
65(1)
6.6.1 Dodging and Burning
65(1)
6.7 Moonrise, Hernandez
66(1)
6.8 Apparent vs. Physical Contrast
66(1)
6.9 Summary
66(2)
6.10 References
68(1)
7 Electronic HDR Image Processing: Analog and Digital
69(8)
7.1 Topics
69(1)
7.2 Introduction
69(1)
7.3 Human Spatial Vision
69(1)
7.4 Electronic HDR Image Processing
70(4)
7.4.1 The Black and White Mondrian
70(1)
7.4.2 Analog Electronic Spatial Rendering
71(2)
7.4.3 Digital Electronic Spatial Rendering
73(1)
7.4.4 Electronic HDR Pixel Processing
74(1)
7.5 Summary
74(1)
7.6 References
75(2)
8 HDR and the World of Computer Graphics
77(6)
8.1 Topics
77(1)
8.2 Introduction
77(1)
8.3 Early Years: the 60s
78(1)
8.4 Early Digital Image Synthesis: the 70s
78(1)
8.5 The Turning Point: the 80s
79(1)
8.6 Computational Photorealism: from the 90s
80(1)
8.7 Summary
80(1)
8.8 References
81(2)
9 Review of HDR History
83(6)
9.1 Topics
83(1)
9.2 Summary of Disciplines
83(1)
9.3 Review
84(3)
9.4 Summary
87(1)
9.5 References
87(2)
Section B MEASURED DYNAMIC RANGES
89(34)
10 Actual Dynamic Ranges
91(8)
10.1 Topics
91(1)
10.2 Introduction
91(1)
10.3 Dynamic Range of Light Sensors
92(1)
10.4 Bits per Pixel
93(1)
10.5 Dynamic Range of Display Devices
94(1)
10.6 Interactions of Pixels in Images
95(1)
10.6.1 Capture to Reproduction
95(1)
10.6.2 Reproduction to Perception
96(1)
10.7 Summary
96(1)
10.8 References
96(3)
11 Limits of HDR Scene Capture
99(14)
11.1 Topics
99(1)
11.2 Introduction
99(1)
11.3 HDR Test Targets
99(2)
11.4 Camera Veiling Glare Limits
101(6)
11.4.1 Digital Camera Response
101(1)
11.4.2 Measurements of Luminous Flux on the Camera's Image Plane (1scaleBlack)
102(1)
11.4.3 Measurements of Luminous Flux on the Camera's Image Plane (4scaleBlack)
103(1)
11.4.4 Measurements of Luminous Flux on the Camera's Image Plane (4scaleWhite)
104(1)
11.4.5 Errors in Estimated Scene Luminance
105(2)
11.5 Glare in Film Cameras
107(4)
11.5.1 Duplication Film-Camera Response
107(1)
11.5.2 Negative Film-Camera Response
107(3)
11.5.3 Pinhole-Camera Response
110(1)
11.6 Review
111(1)
11.7 Summary
111(1)
11.8 References
112(1)
12 Limits of HDR in Humans
113(6)
12.1 Topics
113(1)
12.2 Introduction
113(1)
12.3 Visual Appearance of HDR Displays
113(3)
12.4 von Honthorst's Painting and the 4scaleBlack HDR Target
116(1)
12.5 HDR Displays and Black and White Mondrian
116(1)
12.6 HDR and Tone Scale Maps
117(1)
12.7 HDR Displays and Contrast
117(1)
12.8 Summary
117(1)
12.9 References
118(1)
13 Why Does HDR Improve Images?
119(4)
13.1 Topics
119(1)
13.2 Introduction
119(1)
13.3 Why are HDR Images Better?
120(1)
13.4 Are Multiple Exposures Necessary?
120(1)
13.5 Summary
121(1)
13.6 References
121(2)
Section C SEPARATING GLARE AND CONTRAST
123(50)
14 Two Counteracting Mechanisms: Glare and Contrast
125(10)
14.1 Topics
125(1)
14.2 Introduction
125(1)
14.3 Two Spatial Mechanisms
126(1)
14.4 Calculated Retinal Image
126(5)
14.4.1 Making a Standard Lightness Scale
127(1)
14.4.2 Scatter Calculation
128(1)
14.4.3 Results of Scatter Calculations
129(1)
14.4.4 Retinal Contrast with Different Backgrounds
130(1)
14.4.5 Stiehl et al.'s Conclusions
131(1)
14.5 Measuring the Range of HDR Appearances
131(1)
14.6 Calculating the Retinal Image
131(1)
14.7 Visualizing the Retinal Image
131(1)
14.8 HDR and Uniform Color Space
132(1)
14.9 Summary
132(1)
14.10 References
132(3)
15 Measuring the Range of HDR Appearances
135(10)
15.1 Topics
135(1)
15.2 Introduction
135(1)
15.3 Design of Appearance Scale Target
136(2)
15.3.1 Single- and Double-Density Targets
136(2)
15.4 Magnitude Estimation Experiments
138(3)
15.4.1 Average luminance = 50% max luminance
138(1)
15.4.2 Average luminance = 8% max luminance
139(1)
15.4.3 Control Surrounds -- White and Black
140(1)
15.5 Scene Dependent Tone Scale
141(1)
15.6 Glare and Contrast
142(1)
15.7 Summary
143(1)
15.8 References
143(2)
16 Calculating the Retinal Image
145(8)
16.1 Topics
145(1)
16.2 Introduction
145(1)
16.3 Converting Scene Luminance to Retinal Contrast
146(1)
16.4 Calculating Retinal Radiance
146(3)
16.4.1 Scene Contrast -- Input Luminance Array
147(1)
16.4.2 CIE Veiling Glare Standard
147(1)
16.4.3 Calculate Retinal Radiances
147(2)
16.5 Changes in the Retinal Image from Glare
149(1)
16.6 Appearance and Retinal Image
149(2)
16.7 Scene Content and Psychometric Functions
151(1)
16.8 Summary
151(1)
16.9 References
152(1)
17 Visualizing HDR Images
153(8)
17.1 Topics
153(1)
17.2 Introduction
153(1)
17.3 Calculated Retinal Image Contrast
154(1)
17.4 Retinal Image Contrast
155(4)
17.5 Summary
159(1)
17.6 References
159(2)
18 HDR and Uniform Color Spaces
161(8)
18.1 Topics
161(1)
18.2 Introduction
161(1)
18.3 Uniform Color Spaces -- Psychophysics
161(3)
18.4 Color Vision -- Physiology
164(1)
18.4.1 Spectral Sensitivity
164(1)
18.4.2 Intensity Response
164(1)
18.5 Accurate Transformations from CMF to UCS
165(2)
18.5.1 Data-based LUT Transformations from CMF to UCS
166(1)
18.5.2 Data-based Fit for Transformation from CMF to UCS
166(1)
18.6 Summary
167(1)
18.7 References
168(1)
19 Glare: A Major Part of Vision Theory
169(4)
19.1 Topics
169(1)
19.2 Introduction
169(1)
19.3 Glare: Distorts Lightness below Middle Gray, More or Less
169(1)
19.4 Pixel-based HDR Image Processing
170(1)
19.5 Summary
171(1)
19.6 References
171(2)
Section D SCENE CONTENT CONTROLS APPEARANCE
173(48)
20 Scene Dependent Appearance of Quanta Catch
175(4)
20.1 Topics
175(1)
20.2 Introduction
175(1)
20.3 Models of Vision -- A Choice of Paradigms
175(1)
20.4 Illumination, Constancy and Surround
176(1)
20.5 Maximum's Enclosure and Distance
176(1)
20.6 Size of Maxima
177(1)
20.7 Assimilation
177(1)
20.8 Maxima and Contrast with Maxima
177(2)
21 Illumination, Constancy and Surround
179(14)
21.1 Topics
179(1)
21.2 Introduction
179(1)
21.3 Hipparchus of Nicea
180(2)
21.3.1 Magnitude Estimation of Brightness
180(2)
21.4 Flat-2-D Transparent Displays
182(1)
21.4.1 Experiments
182(1)
21.4.2 Results
183(1)
21.5 A Simple Two-Step Physical Description
183(2)
21.6 Complex 3-D Scenes
185(4)
21.6.1 Experiments
186(1)
21.6.2 Results
187(1)
21.6.3 Do Uniform Stimuli Appear Uniform?
188(1)
21.7 Local Maxima
189(1)
21.8 Review
190(1)
21.9 Summary
190(1)
21.10 References
191(2)
22 Maximum's Enclosure and Separation
193(8)
22.1 Topics
193(1)
22.2 Introduction
193(1)
22.3 Experimental Design
194(1)
22.4 Lightness Matches -- Light Gray on Black
194(1)
22.5 Lightness Matches -- Dark Gray on Black
195(2)
22.5.1 Dark Gray on Black -- White on Four Sides
196(1)
22.5.2 Dark Gray on Black -- White on Three Sides
196(1)
22.5.3 Dark Gray on Black -- White on Two Sides
196(1)
22.5.4 Dark Gray on Black -- White on One Side
196(1)
22.5.5 Dark Gray on Black
196(1)
22.6 Dark Gray on Black: Varying White's Position
197(1)
22.7 Review
198(1)
22.8 Summary
199(1)
22.9 References
200(1)
23 Maxima Size and Distribution
201(8)
23.1 Topics
201(1)
23.2 Introduction
201(1)
23.3 Experimental Procedure
202(1)
23.4 Controls
202(1)
23.5 Dispersion of White ("Snow")
202(1)
23.6 Sides and Corners
203(1)
23.7 Lines
204(1)
23.8 Equivalent Backgrounds
205(2)
23.9 Equivalent Backgrounds and Models of Vision
207(1)
23.10 Summary
207(1)
23.11 References
208(1)
24 From Contrast to Assimilation
209(8)
24.1 Topics
209(1)
24.2 Introduction
209(1)
24.3 Segmented Surrounds
210(5)
24.3.1 56 Combinations
211(1)
24.3.2 Combinations with Four White and Four Black Squares
212(3)
24.4 Checkerboard Variants
215(1)
24.5 Summary
216(1)
24.6 References
216(1)
25 Maxima and Contrast with Maxima
217(4)
25.1 Topics
217(1)
25.2 Merger of Aperture and Object Modes
217(1)
25.2.1 Appearance of Maxima
217(1)
25.2.2 Contrast with Maxima
217(1)
25.3 Influence of the Maxima
218(1)
25.3.1 Take Away the Maximum
218(1)
25.3.2 Phenomena Names vs. Scene Content
218(1)
25.4 Summary
219(2)
Section E COLOR HDR
221(62)
26 HDR, Constancy and Spatial Content
223(4)
26.1 Topics
223(1)
26.2 Introduction
223(1)
26.3 Red and White Projections
224(1)
26.3.1 Maxwell's Three-Color Projectors
224(1)
26.3.2 Colors from Red and White Projections
225(1)
26.4 Color Mondrians
225(1)
26.5 Constancy's On/Off Switch
225(1)
26.6 Color of 3-D Mondrians -- LDR/HDR Illumination
226(1)
26.7 Color Constancy is HDR
226(1)
26.8 References
226(1)
27 Color Mondrians
227(20)
27.1 Topics
227(1)
27.2 Introduction
227(2)
27.2.1 Land's Study of Complex Images
228(1)
27.3 Color Mondrians
229(8)
27.3.1 Land's Original Color Mondrian
229(4)
27.3.2 Quantitative Color Mondrians
233(2)
27.3.3 Physical Correlate of Color Constancy
235(2)
27.3.4 Predicted Color Constancy
237(1)
27.4 The Signature of Color Constancy
237(3)
27.4.1 Incomplete Adaptation Predictions
239(1)
27.4.2 Spatial-Comparisons Predictions
240(1)
27.4.3 Predictions vs. Observed Color Constancy
240(1)
27.5 Search for Evidence of Adaptation -- Averages
240(3)
27.5.1 Search for Global Adaptation
241(1)
27.5.2 Search for Local Adaptation
242(1)
27.5.3 No Evidence of Adaptation in Mondrians
242(1)
27.5.4 Change Adaptation by Changed Average Radiance in Mondrians
242(1)
27.6 Transparency in Mondrians
243(1)
27.7 Color Assimilation
243(1)
27.8 Summary
244(1)
27.9 References
245(2)
28 Constancy's On/Off Switch
247(10)
28.1 Topics
247(1)
28.2 Introduction
247(1)
28.3 Maximov's Shoe Boxes
247(3)
28.3.1 Control -- Change of Appearance from CC40R to CC40C Illumination
249(1)
28.3.2 Experiment -- Change of Appearance in Shoebox
249(1)
28.4 New Maxima Restores Constancy
250(1)
28.5 Independent L, M, S Spatial Processing
251(2)
28.5.1 Center-Surround Maxima Experiment
251(1)
28.5.2 Center-Surround Target -- Control
252(1)
28.5.3 Center-Surround Target -- Constancy Test Patches
253(1)
28.6 Model Predictions
253(1)
28.6.1 Colorimetry Prediction
253(1)
28.6.2 Retinex Prediction
253(1)
28.7 Center-Surround Target -- Results
253(2)
28.8 Summary
255(1)
28.9 References
256(1)
29 HDR and 3-D Mondrians
257(16)
29.1 Topics
257(1)
29.2 Color Constancy and Appearance
257(1)
29.3 Color Constancy Models
258(1)
29.4 Measuring Changes in Appearance from Changes in Illumination
259(3)
29.4.1 Two Identical 3-D Mondrians
260(1)
29.4.2 Characterization of LDR and HDR Illuminations
261(1)
29.5 Magnitude Estimation Appearance Measurements
262(1)
29.6 Watercolor Rendition Measurements of Appearance
263(3)
29.6.1 Watercolor Reflectances Measurements
264(1)
26.6.2 Illumination Affects Lightness
264(2)
27.6.3 Illumination Affects Chroma
266(1)
29.7 Review of 3-D Mondrian Psychophysical Measurements
266(2)
29.7.1 Discount Illumination
268(1)
29.7.2 Real Paints and Lights
268(1)
29.8 Color Constancy Models
268(2)
29.9 Conclusions
270(1)
29.10 References
271(2)
30 Color Constancy is HDR
273(10)
30.1 Topics
273(1)
30.2 Introduction
273(1)
30.3 Rod Receptors and HDR
274(5)
30.3.1 Duplicity Theory
274(1)
30.3.2 Rod Retinex
274(1)
30.3.3 Rods are Color Receptors
275(1)
30.3.4 Rod Retinex plus L-cone Color Appearance Demonstration
276(2)
30.3.5 Rod Retinex plus L-cone Retinex Color Space
278(1)
30.3.6 Rod Retinex plus L-cone Retinex
278(1)
30.4 Assembling Appearance: Color Constancy, Rod Vision and HDR
279(1)
30.5 Summary
280(1)
30.6 References
280(3)
Section F HDR IMAGE PROCESSING
283(94)
31 HDR Pixel and Spatial Algorithms
285(8)
31.1 Topics
285(1)
31.2 Introduction -- HDR Image Processing Algorithms
285(1)
31.3 One Pixel -- Tone Scale Curves
286(2)
31.3.1 One Pixel -- Histogram
286(1)
31.3.2 One Pixel -- LookUp Tables
287(1)
31.3.3 Using 1-D LookUp Tables for Rendering HDR Scene Captures
287(1)
31.4 Some of the Pixels -- Local Processing
288(1)
31.5 All of the Pixels
289(1)
31.6 All Pixels and Scene Dependent -- The Retinex Extended Family
289(1)
31.7 Retinex Algorithms
290(1)
31.8 ACE Algorithms
290(1)
31.9 Analytical, Computational and Variational Algorithms
290(1)
31.10 Techniques for Analyzing HDR Algorithms
290(1)
31.11 The HDR Story
291(1)
31.12 References
291(2)
32 Retinex Algorithms
293(48)
32.1 Topics
293(1)
32.2 Introduction
293(4)
32.2.1 Three Independent Spatial Retinexes Calculate Three Lightnesses -- 1964
293(1)
32.2.2 Ratio-Product
294(3)
32.3 How to Calculate Lightness Using Ratio-Products
297(4)
32.3.1 Normalization
297(1)
32.3.2 Models that Include the Limitations of Vision
298(1)
32.3.3 Gradient Threshold
298(1)
32.3.4 Reset
299(1)
32.3.5 Average Old and New Products
300(1)
32.3.6 Scene Dependent Output
301(1)
32.3.7 Models Using Imposed Limits in Computation
301(1)
32.4 A Variety of Processing Networks
301(1)
32.5 Image Content
302(5)
32.5.1 Normalization in Vision -- Neither Local, Nor Global
303(2)
32.5.2 Tools to Control a Response to Scene Content
305(1)
32.5.3 Edges and Gradients
305(2)
32.6 Real Images -- 1975
307(12)
32.6.1 Real Images in Real Time
308(3)
32.6.2 Goal: Lightness Field Replaces Reflectance
311(1)
32.6.3 Dynamic Range Compression from Threshold or Reset
312(1)
32.6.4 Retinex and Lightness Field Hardware
312(3)
32.6.5 Spatial Processing is in the Middle of the Imaging Chain
315(1)
32.6.6 Zoom Processing
315(4)
32.7 The Extended Family of Retinex Models
319(15)
32.7.1 Land's Designator 1983
319(2)
32.7.2 NASA Retinex 1996
321(1)
32.7.3 Color Gamut Retinex 1999
322(2)
32.7.4 Brownian Path Retinex
324(2)
32.7.5 Random Spray Retinex
326(1)
32.7.6 Different Properties of Locality
326(3)
32.7.7 Sobol's Digital Flash Retinex 2002
329(5)
32.8 Algorithm's Goal
334(3)
32.8.1 Reflectance and Illumination
335(2)
32.9 References
337(4)
33 ACE Algorithms
341(12)
33.1 Topics
341(1)
33.2 Introduction
341(1)
33.3 ACE Algorithm
341(3)
33.3.1 ACE Stage 1
342(2)
33.3.2 ACE Stage 2
344(1)
33.4 Retinex and ACE
344(1)
33.5 ACE Characteristics
345(4)
33.5.1 ACE uses GrayWorld
346(1)
33.5.2 ACE- De-quantization
346(1)
33.5.3 ACE on Simultaneous Contrast and Mach Bands
347(1)
33.5.4 Efficient ACE Processing
348(1)
33.6 RACE
349(1)
33.6.1 ACE with Sprays
349(1)
33.6.2 RACE Formula
349(1)
33.7 Other Vision-based Models
350(1)
33.8 Summary
350(1)
33.9 References
351(2)
34 Analytical, Computational and Variational Algorithms
353(6)
34.1 Topics
353(1)
34.2 Introduction
353(1)
34.3 Math in the Framework of the Human Visual System
354(1)
34.4 Analytical Retinex Formulas
354(1)
34.5 Computational Retinex in Wavelets
354(1)
34.6 Retinex and the Variational Techniques
355(1)
34.7 Summary
356(1)
34.8 References
357(2)
35 Evaluation of HDR Algorithms
359(14)
35.1 Topics
359(1)
35.2 Introduction
359(1)
35.3 Quantitative Approaches to Algorithm Evaluation
360(1)
35.4 Lightness Test Targets
361(1)
35.5 Ratio Metric
362(5)
35.5.1 Spatial Color Metric
362(3)
35.5.2 Experiment in Munsell Space
365(2)
35.6 Quantitative Evaluation of 3-D Mondrians
367(2)
35.6.1 Rendition Quality Metric
367(1)
35.6.2 3-D Mondrians
367(1)
35.6.3 Spatial Color Examples
367(1)
35.6.4 Evaluations of LDR and HDR 3-D Mondrians
368(1)
35.7 Locality Test Targets
369(1)
35.8 Summary
370(1)
35.9 Lessons From Quantitative Studies of HDR in Cameras
371(1)
35.10 References
371(2)
36 The HDR Story
373(4)
36.1 Topic
373(1)
36.2 Straightforward Technology Stories
373(1)
36.3 The HDR Story is Defined by Limits
373(1)
36.4 HDR Works Well
374(1)
36.5 References
375(2)
Glossary 377(8)
Author Index 385(2)
Subject Index 387
John J. McCann, Consultant, McCann Imaging, USA John McCann received a B.A. degree in Biology from Harvard University in 1964. He worked in, and later managed, the Vision Research Laboratory at Polaroid from 1961 to 1996. He has studied human color vision, digital image processing, large format instant photography and the reproduction of fine art. His 120 publications have studied Retinex theory, color from rod/Lcone interactions at low light levels, appearance with scattered light, and HDR imaging. He has been a Fellow of the Society of Imaging Science and Technology (IS&T) since 1983. He is a past President of IS&T and the Artists Foundation, Boston. In 1996 he received the SID Certificate of Commendation. He is the IS&T/OSA 2002 Edwin H. Land Medalist, and IS&T 2005 Honorary Member, and is a 2008 Fellow of the Optical Society of America. He is currently consulting and continuing his research on color vision.

Alessandro Rizzi, Università degli Studi di Milano, Italy Professor Alessandro Rizzi holds a degree in Computer Science at University of Milano and received a PhD in Information Engineering at University of Brescia (Italy). He taught Information Systems and Computer Graphics at University of Brescia and at Politecnico di Milano. He is currently an  assistant professor teaching Multimedia and Human-Computer Interaction, and senior research fellow at the Department of Information Technologies at University of Milano. Since 1990 he has researched in the field of digital imaging and vision. His main research topic is the use of color information in digital images with particular attention to color perception mechanisms. He is the coordinator of the Italian Color Group Conference Chair of Color Conference at IS&T/SPIE Electronic Imaging, and a principle organizer of European Marie Curie Project CREATE.
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