A novel approach for image focus measure

In this paper, a new no-reference image quality assessment (NR-IQA) metric is proposed. This method is based on the probability coefficients and modified entropy. The probability coefficients are used to capture the significant features and represent the important dynamics of an image. Moreover, it is used to quantify the possible loss of naturalness in a distorted image. The proposed approach has been tested on synthetic images with blurring effects and under noisy conditions. It is observed that the proposed focus measure is invariant to contrast and noisy conditions. The effectuality of the proposed approach is tested on various experimentations carried out on real-time images. The performance of proposed focus measure is better as compared to the existing image focus metrics. It also shows a good consistency and a better response under blurring effects and noises at different levels. Moreover, it exhibits a good working range, unimodality and monotonicity properties and hence satisfying the conditions of a good focus measure. Further, the various experiments on image datasets such as LIVE, TID2008 and CSIQ have shown the effectiveness of proposed NR-IQA metric. It is also observed that the presented approach has good correlation with the human opinion score as compared to the existing methods.