Paper
18 January 2010 Evaluation of the visual performance of image processing pipes: information value of subjective image attributes
G. Nyman, J. Häkkinen, E.-M. Koivisto, T. Leisti, P. Lindroos, O. Orenius, T. Virtanen, T. Vuori
Author Affiliations +
Proceedings Volume 7529, Image Quality and System Performance VII; 752905 (2010) https://doi.org/10.1117/12.839946
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Abstract
Subjective image quality data for 9 image processing pipes and 8 image contents (taken with mobile phone camera, 72 natural scene test images altogether) from 14 test subjects were collected. A triplet comparison setup and a hybrid qualitative/quantitative methodology were applied. MOS data and spontaneous, subjective image quality attributes to each test image were recorded. The use of positive and negative image quality attributes by the experimental subjects suggested a significant difference between the subjective spaces of low and high image quality. The robustness of the attribute data was shown by correlating DMOS data of the test images against their corresponding, average subjective attribute vector length data. The findings demonstrate the information value of spontaneous, subjective image quality attributes in evaluating image quality at variable quality levels. We discuss the implications of these findings for the development of sensitive performance measures and methods in profiling image processing systems and their components, especially at high image quality levels.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
G. Nyman, J. Häkkinen, E.-M. Koivisto, T. Leisti, P. Lindroos, O. Orenius, T. Virtanen, and T. Vuori "Evaluation of the visual performance of image processing pipes: information value of subjective image attributes", Proc. SPIE 7529, Image Quality and System Performance VII, 752905 (18 January 2010); https://doi.org/10.1117/12.839946
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Cited by 9 scholarly publications.
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KEYWORDS
Image quality

Image processing

Molybdenum

Image analysis

Visualization

Cameras

Signal processing

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