English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Many interpolation methods have been developed for high visual quality, butfail for inability to preserve image structures. Edges carry heavy structuralinformation for detection, determination and classification. Edge-adaptiveinterpolation approaches become a center of focus. In this paper, performanceof four edge-directed interpolation methods comparing with two traditionalmethods is evaluated on two groups of images. These methods include newedge-directed interpolation (NEDI), edge-guided image interpolation (EGII),iterative curvature-based interpolation (ICBI), directional cubic convolutioninterpolation (DCCI) and two traditional approaches, bi-linear and bi-cubic.Meanwhile, no parameters are mentioned to measure edge-preserving ability ofedge-adaptive interpolation approaches and we proposed two. One evaluatesaccuracy and the other measures robustness of edge-preservation ability.Performance evaluation is based on six parameters. Objective assessment andvisual analysis are illustrated and conclusions are drawn from theoreticalbackgrounds and practical results.

Performance Evaluation of Edge-Directed Interpolation Methods for Images