A Blind Image Quality Assessment With Globally and Locally Consilient Visual Quality Perception
M. Prasanna · Journal of Emerging Technologies and Innovative Research · 2017
Most of the existing Blind image quality assessment techniques can hardly characterize visual quality perception for various distortion types. The different blind image quality assessment algorithms cannot correlate with full-reference image quality assessment techniques. So, in this paper we first perform image quality assessment for the full-reference images on different distortion types and then the quality of the distorted image is found by using the Blind image quality assessment technique. The performance of the blind image quality assessment is compared with the performance of the full-reference image quality assessment techniques. This paper focuses on the measurement of quality for the distorted images which are used in the measurement of performance of the full-reference images. The experimental results show that algorithm exhibits high correlation with the novel full-reference image quality metrics when compared with the other Blind image quality metrics.