چکیده (انگلیسی):

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.