PATH VS. DESTINATION: A CASE STUDY OF BLIND NOISE ASSESSMENT USING MODIFIED ANT SHORTEST PATH

Blind noisy assessment aims to evaluate the quality of the degraded noisy image/video without the need for the ground-truth image. To tackle this challenge, this paper proposes a new blind noise assessment approach based on the path information of the ants' movement. The proposed modified ant shortest path (MASP) algorithm uses the path information of the ant colony optimization (ACO). The contribution of the proposed approach is two-fold. First, the proposed approach utilizes a number of artificial ants to move on a 2-D graph for constructing the path information, and calculates the ants' movement path driven by the shortest path strategy. Second, several path statistics metrics are proposed to evaluate the image quality. Experimental results are provided to demonstrate that the proposed image quality assessment approach is effective for both benchmark image database and real-world noisy video.