Quality Evaluation for Adaptive Optical Image through a Logarithmic Deviation of Renyi Entropy

The adaptive optical telescopes play a more and more important role in astronomy and satellite detection, and the space target images are so many that we need find a suitable method of quality evaluation to choose good quality images automatically in order to study the restorate image. It is well known that the adaptive optical images are no-referrence images. In this paper, a new evaluation method based on the use of the logarithmic standard deviation of Renyi Entropy for the adaptive optical images is proposed. Through the discrete cosine transform using one dimension window, the statistical property of Renyi entropy for images is studied. The different directional Renyi entropy maps of an input image containing different information content are obtained. The mean values of different directional Renyi entropy maps are calculated. For image quality evaluation, the different directional Renyi entropy and its standard deviation corresponding to region of interest is selected as an indicator for the anisotropy of the images. In this paper, we define a logarithmic measure the standard deviation based on Renyi entropy can be selected as an indicator of quality evaluation for adaptive optical images. Experimental results show the proposed method that the sorting quality matches well with the visual inspection.