An image quality assessment metric based on Non-shift Edge
Wufeng Xue, Xuanqin Mou · 2011
In this paper, we propose a novel metric for image quality assessment based on the ratio of Non-shift Edge (rNSE), whose elegance lies in succinctness and effectiveness. In this metric, an image is filtered by the LOG operator, who acts like the classical receptive field, and the edge points are detected as the zero-crossings of the filtered image. Then the binary Non-shift Edge (NSE) map is derived to represent the strong edge structure remained in the distorted image. The perceptual quality is calculated by the ratio of NSE. The performance of rNSE in the scale-threshold plane shows similar frequency and threshold selectivity. Comparing with the existing well-designed metrics, the proposed rNSE performs equivalently in accuracy and consistency.