Approximate image quality measure in low-dimensional domain based on random projection

Document Type

Article

Publication Date

3-1-2008

Abstract

Image Quality Measure (IQM) is used to automatically measure the degree of image artifacts such as blocking, ringing and blurring effects. It is calculated traditionally in the image spatial domain. In this paper, we present a new method of transforming an image into a low-dimensional domain based on random projection, so we can efficiently obtain the compatible IQM. From the transformed domain, we can calculate the Peak Signal-to-Noise Ratio (PSNR) and apply fuzzy logic to generate a Low-Dimensional Quality Index (LDQI). Experimental results show that the LDQI can approximate the IQM in the image spatial domain. We observe that the LDQI is suited for measuring the compression blur due to its relatively low distortion. The relative error is about 0.15 as the compression blur increases. © 2008 World Scientific Publishing Company.

Identifier

44349171733 (Scopus)

Publication Title

International Journal of Pattern Recognition and Artificial Intelligence

External Full Text Location

https://doi.org/10.1142/S0218001408006235

ISSN

02180014

First Page

335

Last Page

345

Issue

2

Volume

22

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