Image Quality Assessment Employing RMS Contrast and Histogram Similarity

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).