IEEE 3333.1.4-2022
IEEE Recommended Practice for the Quality Assessment of Light Field Imaging
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About This Item
IEEE 3333.1.4-2022 is a recommended practice for the quality assessment of light field imaging, bringing a structured approach to evaluating image capture and processing results. It is relevant to computing and processing workflows as well as photonics and electrooptics applications where light field data must be judged for consistency, fidelity, and practical usability. For teams working with this imaging format, IEEE 3333.1.4-2022 helps define a more reliable basis for testing and comparison.
What is IEEE 3333.1.4-2022?
This technical document addresses how the quality of light field imaging may be assessed in a repeatable and meaningful way. As a recommended practice, IEEE 3333.1.4-2022 is intended to support evaluation methods for light field capture, rendering, and related processing steps rather than to define a single product design. Its value lies in helping users and developers apply consistent quality criteria when working with complex multi-view or computational imaging content.
Where is IEEE 3333.1.4-2022 used?
IEEE 3333.1.4-2022 is typically used in light field imaging systems and related computational imaging workflows where quality checking is needed during development, testing, or validation. It may be relevant to imaging equipment, optical capture setups, display pipelines, and software that handles light field reconstruction or analysis. In practice, it can support work in laboratories, product engineering, and other settings where accurate assessment of rendered or captured light field results matters.
Why is IEEE 3333.1.4-2022 important?
This standard matters because quality assessment for light field imaging can be difficult without a common reference point. IEEE 3333.1.4-2022 helps improve consistency in testing, comparison, and procurement decisions by giving stakeholders a clearer way to judge performance. It can also reduce ambiguity between capture systems, processing methods, and evaluation results, which is useful when teams need repeatable outcomes and defensible technical decisions.
- Quality assessment for light field imaging
- Computational imaging and processing context
- Evaluation of capture and rendering results
- Useful for testing, validation, and comparison
- Relevant to optical and imaging system workflows
- Publication Date: 2023
- Standard Status: Active
- Publisher: IEEE
- Subject: Computing and Processing; Photonics and Electrooptics
- Official IEEE: Doi link
- This Version: 3333.1.4 (2023)
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