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Predicting image quality using a modular image difference model

Orfanidou, Maria and Triantaphillidou, Sophie and Allen, Elizabeth (2008) Predicting image quality using a modular image difference model. In: Farnand, Susan P. and Gaykema, Frans, (eds.) Image quality and system performance V : 28-30 January 2008, San Jose, California, USA. Proceedings of SPIE (6808). IS&T - The Society for Imaging and Science and Technology and SPIE, F1-F12. ISBN 9780819469809

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Official URL: http://dx.doi.org/10.1117/12.766407


The paper is focused on the implementation of a modular color image difference model, as described in [1], with aim to predict visual magnitudes between pairs of uncompressed images and images compressed using lossy JPEG and JPEG 2000. The work involved programming each pre-processing step, processing each image file and deriving the error map, which was further reduced to a single metric. Three contrast sensitivity function implementations were tested; a Laplacian filter was implemented for spatial localization and the contrast masked-based local contrast enhancement method, suggested by Moroney, was used for local contrast detection. The error map was derived using the CIEDE2000 color difference formula on a pixel-by-pixel basis. A final single value was obtained by calculating the median value of the error map. This metric was finally tested against relative quality differences between original and compressed images, derived from psychophysical investigations on the same dataset. The outcomes revealed a grouping of images which was attributed to correlations between the busyness of the test scenes (defined as image property indicating the presence or absence of high frequencies) and different clustered results. In conclusion, a method for accounting for the amount of detail in test is required for a more accurate prediction of image quality.

Item Type:Book Section
Research Community:University of Westminster > Electronics and Computer Science, School of
ID Code:8953
Deposited On:16 Dec 2010 13:15
Last Modified:16 Dec 2010 13:28

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