A New Objective Image Quality Assessment Metric: For Color and Grayscale Images

Image quality assessment (IQA) is a challenging task in digital image processing where the images get distorted in several situations. In recent years, various IQA measures have been developed to assess the quality of images in subjective and objective manner. Although the popular measures like mean square error (MSE) and peak signal to noise ratio (PSNR) work well for grayscale images, they fail to measure the exact difference between two color images on a pixel by pixel basis. To overcome this problem, we made a slight modification in the MSE and PSNR to present new measures mean absolute variance and fidelity ration (FR). Moreover, we formulate a constant ‘ k ’ of value 9.542425094 to establish a relationship between FR of color and grayscale images. The performance of the proposed metric is validated by comparing its results with state of art metrics against a same set of benchmark dataset. Though the proposed method involves simple mathematical calculations and no human visual system model is employed, the experimental analysis shows that FR is found to be highly effective and robust measure especially for continuous tone, discrete tone, bi-level and inverted images. This measure is highly useful for applications require exact IQA where a change of one-pixel value is also not desirable.