Saliency change based reduced reference image quality assessment
The image quality assessment (IQA) technique, which aims to perform coherently with subjective perception, is useful in quality-orientated image processing systems. In this paper, we suggest to take the saliency change into account for reduced reference (RR) IQA model. Generally, a saliency region will attract more attention, and our human vision is more sensitive to quality degradation on such region. Inspired by this, saliency values are firstly used to highlight these sensitive regions, and a local saliency weighted histogram (LSWH) based on visual orientation pattern is generated for visual feature extraction. Next, strong distortion may change the saliency from the reference to the distorted images. Thus, the saliency of each visual orientation pattern is measured, and a global saliency based histogram (GSBH) is created. Finally, by combining the LSWH and GSBH, a novel IQA model for reduced reference is introduced. Experimental results on five publicly available databases demonstrate that the proposed model uses only several values (9 values) as reference information, and performs consistently with subjective perception.