Document Type

Journal Article

Publisher

Science Publications

Faculty

Faculty of Health, Engineering and Science

School

School of Engineering

RAS ID

18453

Comments

This article was originally published as: Hassan A.F., Cai-lin D., Hussain Z.M. (2014). An information-theoretic image quality measure: Comparison with statistical similarity. Journal of Computer Science, 10(11), 2269-2283. Original article available here

Abstract

We present an information-theoretic approach for structural similarity for assessing gray scale image quality. The structural similarity measure SSIM, proposed in 2004, has been successflly used and verfied. SSIM is based on statistical similarity between the two images. However, SSIM can produce confusing results in some cases where it may give a non-trivial amount of similarity for two different images. Also, SSIM cannot perform well (in detecting similarity or dissimilarity) at low peak signal to noise ratio (PSNR). In this study, we present a novel image similarity measure, HSSIM, by using information - theoretic technique based on joint histogram. The proposed method has been tested under Gaussian noise. Simulation results show that the proposed measure HSSIM outperforms statistical similarity SSIM by ability to detect similarity under very low PSNR. The average difference is about 20dB.

DOI

10.3844/jcssp.2014.2269.2283

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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