Open source database of images DEIMOS: extension for large-scale subjective image quality assessment

Stanislav Vítek

doi:10.1117/12.2061369

23 September 2014 Open source database of images DEIMOS: extension for large-scale subjective image quality assessment

Stanislav Vítek

Proceedings Volume 9217, Applications of Digital Image Processing XXXVII; 92170J (2014) https://doi.org/10.1117/12.2061369
Event: SPIE Optical Engineering + Applications, 2014, San Diego, California, United States

Abstract

DEIMOS (Database of Images: Open Source) is an open-source database of images and video sequences for testing, verification and comparison of various image and/or video processing techniques such as compression, reconstruction and enhancement. This paper deals with extension of the database allowing performing large-scale web-based subjective image quality assessment. Extension implements both administrative and client interface. The proposed system is aimed mainly at mobile communication devices, taking into account advantages of HTML5 technology; it means that participants don’t need to install any application and assessment could be performed using web browser. The assessment campaign administrator can select images from the large database and then apply rules defined by various test procedure recommendations. The standard test procedures may be fully customized and saved as a template. Alternatively the administrator can define a custom test, using images from the pool and other components, such as evaluating forms and ongoing questionnaires. Image sequence is delivered to the online client, e.g. smartphone or tablet, as a fully automated assessment sequence or viewer can decide on timing of the assessment if required. Environmental data and viewing conditions (e.g. illumination, vibrations, GPS coordinates, etc.), may be collected and subsequently analyzed.

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Stanislav Vítek "Open source database of images DEIMOS: extension for large-scale subjective image quality assessment", Proc. SPIE 9217, Applications of Digital Image Processing XXXVII, 92170J (23 September 2014); https://doi.org/10.1117/12.2061369

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KEYWORDS

Databases

Image quality

Video

Multimedia

Video processing

Sensors

Video compression

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