AN INFORMATION-THEORETIC IMAGE QUALITY MEASURE: COMPARISON WITH STATISTICAL SIMILARITY | Science Publications

Journal of Computer Science

Dong Cai-lin¹  Asmhan Flieh Hassan¹  Zahir M. Hussain¹ 

关键词: Joint Histogram;    Image Structural Similarity;    Image Quality Assessment;    Image Processing;   

DOI  :  10.3844/jcssp.2014.2269.2283

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

Unknown