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Released: 04.08.2023
IEEE 1858-2023 - IEEE Standard for Camera Phone Image Quality (CPIQ)
IEEE Standard for Camera Phone Image Quality (CPIQ)
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English PDF
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151.63 EUR
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Standard number: | IEEE 1858-2023 |
Released: | 04.08.2023 |
ISBN: | 978-1-5044-9720-6 |
Pages: | 170 |
Status: | Active |
Language: | English |
DESCRIPTION
IEEE 1858-2023
This standard addresses the fundamental attributes that contribute to video and still image quality, as well as identifying existing metrics and other useful information relating to these attributes. It defines a standardized suite of objective and subjective test methods for measuring camera phone image quality attributes, and it specifies tools and test methods to facilitate standards-based communication and comparison among carriers, handset manufacturers, and component vendors regarding camera phone image quality.Camera-equipped mobile devices have become ubiquitous, displacing dedicated digital cameras as many users’ primary tools for photography. However, consumers have little guidance about the quality of the images produced by particular device models. That lack of guidance is due in part to a lack of uniform image quality testing for the devices, and what testing is done seldom is accessible to the layperson. This standard attempts to establish a uniform means of evaluating the quality of cameras in mobile devices, allowing objective comparison between devices, models, and manufacturers, using a variety of metrics that are relevant to consumer photography.
Revision 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., digital single lens reflexes (DSLRs)]. Metrics include spatial frequency response, color uniformity, chroma level, lateral chromatic displacement, local geometric distortion, texture blur, and visual noise.