Blind image quality assessment for color images with additive Gaussian white noise using standard deviation
Chern-Loon Lim, Raveendran Paramesran · 2014
This paper presents a no-reference (NR) quality assessment method for color images contaminated with additive Gaussian white noise (AGWN). The proposed metric operates on the test image and the scaled down version of the test image. Standard deviations for each of the RGB components for the test image and its scaled down version are computed. The standard deviation ratios of the scaled down version image to the original test image are weighted summed to obtain the quality score for noise. The performance of the proposed metric is compared with existing full-reference (FR) and NR metrics on LIVE database. Pearson correlation coefficient (CC), mean absolute error (MAE) and root mean square error (RMSE) are used to evaluate the performance of the proposed metric. A CC score of 0.9785 shows that the proposed metric has high correlation with the subjective scores for the LIVE database.