Handbook of Image Quality

Characterization and Prediction

AvBrian Keelan

Inbunden, Engelska, 2002

Del i serien Optical Science and Engineering

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Beskrivning

With 300 figures, tables, and equations, this book presents a unified approach to image quality research and modeling. The author discusses the results of different, calibrated psychometric experiments can be rigorously integrated to construct predictive software using Monte Carlo simulations and provides numerous examples of viable field applications for product design and verification of modeling predictions. He covers perceptual measurements for the assessment of individual quality attributes and overall quality, explores variation in scene susceptibility, observer sensitivity, and preference, and includes methods of analysis for testing and refining metrics based on psychometric data.

Produktinformation

Utgivningsdatum:2002-03-21
Mått:152 x 229 x 36 mm
Vikt:1 170 g
Format:Inbunden
Språk:Engelska
Serie:Optical Science and Engineering
Antal sidor:544
Förlag:Taylor & Francis Inc
ISBN:9780824707705

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Recensioner i media

"This volume presents the first unified approach to image quality research and modelling to have been applied to systems design and verified in practical applications…intended particularly for image scientists and product engineers, but portions of it should prove useful to individuals involved in project management, manufacturing quality control, marketing, business research, systems performance analysis, human factors and usability assessment, trade journal evaluations, and standard definitions. It is hoped that this publication will focus new attention on, and stimulate further advances in, the fascinating field of image quality."-Optik, 116 (2005)

Innehållsförteckning

Characterization and quality: can image quality be usefully quantified ; the probablistic nature of perception; just noticable differences; quantifying preference; properties of ideal interval and ratio scales; establishing image quality standards;calibrated psychometrics using quality rulers; practical implementation of quality rulers; a general equation to fit quality loss functions; scene and observer variability; predicting overall quality from image attributes. Design of objective metrics:overview of objective metric properties; testing objective metrics using psychometric data; a detailed example of objective metric design.