Image Quality Assessment Employing RMS
Contrast and Histogram Similarity
Al-Amin Bhuiyan1 and Abdul Raouf
Khan2
1Department of Computer Engineering, King Faisal
University, KSA
2Department
of Computer Science, King Faisal University, KSA
Abstract: This paper presents a new approach for evaluating
image quality. The method is based on the histogram similarity computation
between images and is organized with assessing quality index factors due to the
contributions of correlation
coefficient, average luminance distortion and rms contrast measurement. The
effectiveness of this proposed RMS Contrast and Histogram Similarity (RCHS)
based hybrid quality index has been justified over Lena images under different
well known distortions and standard image databases. Experimental results
demonstrate that this image quality assessment method performs better than those of widely used image
distortion quality metric Mean Squared Error (MSE), Structural
SIMilarity (SSIM) and Histogram based Image Quality (HIQ).
Keywords: Image quality measures, RMS contrast, histogram similarity, SSIM,
HIQ, minkowski distance metric.