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

A feature-preserving non-local means (FP-NLM) filter has been developed recently for denoising images containing small and weak particlelike objects. It explores the commonly used non-local means filter to employ two similarity measurements taken in the original greyscale image and a feature image which measures the particle probability in the original image. In this paper, we report a new approach to image mapping for constructing the feature image by incorporating both spatial and temporal (2D+t) characteristics of objects. We present a 2D+t FP-NLM filter based on the improved particle probability image. Experiments show that the new filter can achieve better balance between particle enhancement and background smoothing for images under severe noise contamination and has a greater capability in detecting particles of interest in such environments.

A 2D+t Feature-preserving Non-local Means Filter for Image Denoising and Improved Detection of Small and Weak Particles