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This paper presents a novel sharpness metric for color images. The proposed metric can be used for no-reference assessment of image visual quality. The metric basically relies on local power of wavelet transform high-frequency coefficients. It also takes into account possibility of presence of macrophotography and portrait photography effects in an image where the image part (usually central one) in sharp whilst the remained part (background) is smeared. Such effects usually increase subjective evaluation of image visual quality by humans. The effects are taken into consideration by joint analysis of wavelet coefficients with largest and smallest squared absolute values. Besides, we propose a simple mechanism for blocking artifact accounting (if an image is compressed by JPEG) and compensation of this factor contribution. Finally, the proposed sharpness metric is calculated in color space YCbCr as a weighted sum of sharpness components. Weight optimization has shown that a weight for intensity component Y is to be considerably smaller than weights for color components Cb and Cr. Optimization of weights for all stages of sharpness metric calculation is carried out for specialized database NRTID that contains 500 test images with previously determined MOS (Mean Opinion Score). Spearman rank order correlation coefficient (SROCC) determined for the designed sharpness metric and MOS is used as optimization criterion. After optimization, it reaches 0.71. This is larger than for other known available no-reference metrics considered at verification stage.

A task of no-reference visual quality metric verification is considered. A test set that contains 500 JPEG format images having different distortions is created. The results of experiments carried out by 316 volunteer observers to evaluate visual quality of images are presented. The experiments allowed obtaining mean opinion scores (MOS) based on averaging the evaluations. Several non-reference image visual quality metrics have been analyzed. Spearman and Kendall correlations between MOS and metrics values are calculated. It is shown that all analyzed metrics have not enough correspondence to human perception.