IEEE 1858 2016:2017 Edition

$80.71

IEEE Standard for Camera Phone Image Quality

Published By	Publication Date	Number of Pages
IEEE	2017	146

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Description

New IEEE Standard – Active. Quantifying the performance of camera-equipped mobile devices is covered in this standard, with an emphasis on metrics and procedures appropriate to the types of sensors, lenses, and signal processing routines present on such devices. It is not intended as a general image quality standard for photographs produced by high-end dedicated cameras, e.g., DSLRs. Metrics include spatial frequency response, color uniformity, chroma level, lateral chromatic displacement, local geometric distortion, texture blur, and visual noise.

PDF Catalog

PDF Pages	PDF Title
1	IEEE Std 1858™-2016 Front Cover
3	Title page
5	Important Notices and Disclaimers Concerning IEEE Standards Documents
8	Participants
10	Introduction
11	Contents
15	1. Overview 1.1 Scope 1.2 Purpose 2. Normative references
16	3. Definitions, acronyms, and abbreviations 3.1 Definitions
17	3.2 Acronyms and abbreviations
19	4. Test conditions and apparatus 4.1 Environment 4.2 Charts
21	4.3 Lighting
23	4.4 Camera settings 5. Spatial frequency response (SFR) 5.1 Introduction 5.2 Scope
24	5.3 Test conditions and methods
29	5.4 Acutance calculation
31	5.5 Subjective evaluation
33	6. Lateral chromatic displacement 6.1 Introduction
34	6.2 Measurements
35	6.3 Test conditions and methods
36	6.4 Analytical approach and presentation of results 6.5 Subjective evaluation
37	7. Chroma level 7.1 Introduction 7.2 Test conditions and methods
39	7.3 Chroma level metric
41	7.4 Subjective evaluation
42	8. Color uniformity 8.1 Introduction
43	8.2 Test conditions and methods
44	8.3 Analytical approach and presentation of results
45	8.4 Subjective evaluation
46	9. Local geometric distortion 9.1 Introduction 9.2 Scope
47	9.3 Definition 9.4 Measurements
48	9.5 Test conditions and methods
49	9.6 Analytical approach and presentation of results
51	9.7 Subjective evaluation
54	10. Visual noise
55	10.1 Scope 10.2 Test conditions and methods
57	10.3 Metric
60	10.4 Caution 10.5 Subjective evaluation 11. Texture blur
61	11.1 Scope 11.2 Background
64	11.3 Test conditions
66	11.4 Caution 11.5 Dead leaves texture acutance metric
68	11.6 Subjective evaluation
71	Annex A (normative) Subjective evaluation methodology A.1 Introduction A.2 Scope A.3 Acceptability scaling
75	A.4 Softcopy quality ruler
79	Annex B (normative) Viewing conditions and conversion to angular spatial frequency
81	Annex C (normative) Slanted edge SFR algorithm C.1 Basic steps C.2 Modification
83	Annex D (normative) Visual noise processing D.1 sRGB to linear sRGB
84	D.2 Linear sRGB to CIE XYZ(D65) D.3 CIE XYZ(D65) to CIE XYZ(E) D.4 CIE XYZ(E) to AC1C2 opponent color space
85	D.5 Pixels/cycle to CPD D.6 Contrast sensitivity function (CSF)
87	D.7 Display/printer MTF D.8 High pass filter (HPF)
88	D.9 Applying the frequency based spatial filtering D.10 AC1C2 opponent color space to CIE XYZ(E)
89	D.11 CIE XYZ (E) to CIE XYZ(D65)
90	D.12 XYZ (D65) to CIELAB D.13 Objective noise
91	Annex E (normative) Steps to calculate texture acutance E.1 Step 1: Linearization E.2 Step 2: Computation of luminance E.3 Step 3: Texture Fourier transform E.4 Step 4: 1D FFT calculation E.5 Step 5: Noise compensation
92	E.6 Step 6: Normalization by the ideal chart power spectrum
93	Annex F (informative) SFR data processing
95	Annex G (informative) Linearization by inversion of gamma curve
97	Annex H (informative) Example acutance calculation
102	Annex I (informative) Color uniformity illustrative example
106	Annex J (informative) Lateral chromatic displacement—illustrative example
108	Annex K (informative) Extracting the dots from the target K.1 Overview
109	K.2 Finding dot ROIs
117	Annex L (informative) Dot center validation L.1 Dot center validation L.2 AMD reference images
118	L.3 DxO Labs reference images
122	Annex M (informative) Local geometric distortion – illustrative example and validation
124	Annex N (informative) Grid sort N.1 Overview N.2 Initialization
125	N.3 Grid creation
131	Annex O (informative) Derivation of objective metric to JND mapping
134	Annex P (informative) Fitting the texture MTF
136	Annex Q (informative) Example texture analysis
139	Annex R (informative) Example texture blur results
141	Annex S (informative) Texture blur chart design
143	Annex T (informative) Subjective data and models
144	Annex U (informative) Bibliography
146	Back Cover