Objective image quality evaluation for JPEG, JPEG 2000, and vidware vision™

Authors:
Chung-Hao Chen;Yi Yao;David L. Page;Besma Abidi;Andreas Koschan;Mongi Abidi
Affiliations:
Imaging, Robotics and Intelligent System Laboratory, The University of Tennessee, Knoxville, Tennessee;Imaging, Robotics and Intelligent System Laboratory, The University of Tennessee, Knoxville, Tennessee;Imaging, Robotics and Intelligent System Laboratory, The University of Tennessee, Knoxville, Tennessee;Imaging, Robotics and Intelligent System Laboratory, The University of Tennessee, Knoxville, Tennessee;Imaging, Robotics and Intelligent System Laboratory, The University of Tennessee, Knoxville, Tennessee;Imaging, Robotics and Intelligent System Laboratory, The University of Tennessee, Knoxville, Tennessee
Venue:
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Year:
2006

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Abstract

In this paper, three compression methods, JPEG, JPEG 2000, and Vidware VisionTM are evaluated by different full- and no-reference objective image quality measures including Peak-Signal-to-Noise-Ratio (PSNR), structural similarity (SSIM), and Tenengrad. In the meantime, we also propose an image sharpness measure, non-separable rational function based Tenengrad(NSRT2), to address whether the compression method is appropriate to be used in a machine recognition application. Based on our experimental results Vidware VisionTM is more robust to changes in compression ratio and presents gradually degraded performance at a considerably slower speed thus outperforming JPEG and JPEG 2000 when the compression ratio is smaller than 0.7%. Furthermore, the effectiveness of our proposed measurement, NSRT2, is also validated via experiments and performance comparisons with other objective image quality measures.