1 research outputs found
Performance Evaluation of Edge-Directed Interpolation Methods for Images
Many interpolation methods have been developed for high visual quality, but
fail for inability to preserve image structures. Edges carry heavy structural
information for detection, determination and classification. Edge-adaptive
interpolation approaches become a center of focus. In this paper, performance
of four edge-directed interpolation methods comparing with two traditional
methods is evaluated on two groups of images. These methods include new
edge-directed interpolation (NEDI), edge-guided image interpolation (EGII),
iterative curvature-based interpolation (ICBI), directional cubic convolution
interpolation (DCCI) and two traditional approaches, bi-linear and bi-cubic.
Meanwhile, no parameters are mentioned to measure edge-preserving ability of
edge-adaptive interpolation approaches and we proposed two. One evaluates
accuracy and the other measures robustness of edge-preservation ability.
Performance evaluation is based on six parameters. Objective assessment and
visual analysis are illustrated and conclusions are drawn from theoretical
backgrounds and practical results.Comment: 9 pages, 5 figures, 2 table