No abstract

No abstract

Abstract. With the development of computer vision, there has been an increasing need to develop objective quality measurement techniques that can predict image quality automatically. In this paper, we present a complex Noreference image quality assessment (NR IQA) algorithm, which mainly consists of two steps. The first step uses Gabor filters to obtain the feature images with different frequencies and orientations, so as to extract the energy and entropy features of each sub-image. The second step uses the Linear least squares to obtain the parameters for IQA. We conduct experiments in LIVE IQA Database to verify our method. The experimental results show that the proposed method is much more competitive than other state of the art Full-reference (FR) or NR algorithms.