IEEE P1858:2023 Edition

$86.13

IEEE Approved Draft Standard for Camera Phone Image Quality (CPIQ)

Published By	Publication Date	Number of Pages
IEEE	2023	170

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Description

Revision Standard – Active – Draft. 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™-2023 Front Cover
2	Title page
4	Important Notices and Disclaimers Concerning IEEE Standards Documents
8	Participants
9	Introduction
10	Contents
13	1. Overview 1.1 Scope 1.2 Purpose 1.3 Word usage
14	2. Normative references
15	3. Definitions, acronyms, and abbreviations 3.1 Definitions
16	3.2 Acronyms and abbreviations
17	4. Test conditions and apparatus 4.1 Environment 4.2 Charts
20	4.3 Lighting
21	4.4 Camera settings 5. Spatial frequency response (SFR) 5.1 Introduction
22	5.2 Scope 5.3 Test conditions and methods
26	5.4 Acutance calculation
27	5.5 Subjective evaluation
29	6. Lateral chromatic displacement 6.1 Introduction
30	6.2 Measurements
31	6.3 Test conditions and methods
32	6.4 Analytical approach and presentation of results 6.5 Subjective evaluation
33	7. Chroma level 7.1 Introduction 7.2 Test conditions and methods
35	7.3 Chroma level metric
37	7.4 Subjective evaluation
38	8. Color uniformity 8.1 Introduction 8.2 Test conditions and methods
40	8.3 Analytical approach and presentation of results 8.4 Subjective evaluation
42	9. Local geometric distortion 9.1 Introduction 9.2 Scope 9.3 Definition
43	9.4 Measurements 9.5 Test conditions and methods
44	9.6 Analytical approach and presentation of results
47	9.7 Subjective evaluation
49	10. Visual noise
50	10.1 Scope 10.2 Test conditions and methods
52	10.3 Metric
54	10.4 Caution
55	10.5 Subjective evaluation 11. Texture blur 11.1 Scope
56	11.2 Background
58	11.3 Test conditions
61	11.4 Caution 11.5 Dead leaves texture acutance metric
62	11.6 Subjective evaluation
64	12. Auto-exposure 12.1 Introduction to exposure determination 12.2 Test conditions and methods
66	12.3 Exposure level metric
67	12.4 Subjective evaluation
69	13. Video metrics
70	13.1 Jitter
72	13.2 Motion blur
76	13.3 Exposure and white balance convergence metrics
78	13.4 Subjective comparison framework (Seungseok et al. [B43])
90	Annex A (normative) Image subjective evaluation methodology A.1 Introduction A.2 Scope A.3 Acceptability scaling
94	A.4 Softcopy quality ruler
98	Annex B (normative) Viewing conditions and conversion to angular spatial frequency
100	Annex C (normative) Slanted edge SFR algorithm C.1 Basic steps C.2 Modification
101	Annex D (normative) Visual noise processing D.1 sRGB to linear sRGB
102	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 D.5 Pixels/cycle to CPD
103	D.6 Contrast sensitivity function (CSF)
105	D.7 Display/printer MTF D.8 High pass filter (HPF)
106	D.9 Applying the frequency based spatial filtering
107	D.10 AC1C2 opponent color space to CIE XYZ(E) D.11 CIE XYZ (E) to CIE XYZ(D65) D.12 XYZ (D65) to CIELAB
108	D.13 Objective noise
109	Annex E (normative) Steps to calculate texture acutance E.1 Step 1: Linearization E.2 Step 2: Computation of luminance E.3 Step 3: Image denoising E.4 Step 4: Texture Fourier transform E.5 Step 5: 1D FFT calculation
110	E.6 Step 6: Normalization by the ideal chart power spectrum
111	Annex F (informative) SFR data processing
113	Annex G (informative) Linearization by inversion of gamma curve
115	Annex H (informative) Example acutance calculation
120	Annex I (informative) Color uniformity illustrative example
124	Annex J (informative) Lateral chromatic displacement—illustrative example
126	Annex K (informative) Extracting the dots from the target K.1 Overview
127	K.2 Finding dot ROIs
135	Annex L (informative) Dot center validation L.1 Dot center validation L.2 AMD reference images
136	L.3 DxO Labs reference images
140	Annex M (informative) Local geometric distortion—Illustrative example and validation
142	Annex N (informative) Grid sort N.1 Overview N.2 Initialization
143	N.3 Grid creation
149	Annex O (informative) Derivation of objective metric to JND mapping
152	Annex P (informative) Fitting the texture MTF
154	Annex Q (informative) Example texture analysis
157	Annex R (informative) Example texture blur results
159	Annex S (informative) Texture blur chart design
161	Annex T (informative) Subjective data and models
162	Annex U (informative) 140 Patch Color Test Card
167	Annex V (informative) Bibliography
170	Back Cover