A Change-Driven Image Foveation Approach for Tracking Plant Phenology

Citation

Silva E, Torres RdS, Alberton B, Morellato LPC & Silva TSF (2020) A Change-Driven Image Foveation Approach for Tracking Plant Phenology. Remote Sensing, 12 (9), Art. No.: 14. https://doi.org/10.3390/rs12091409

Abstract
One of the challenges in remote phenology studies lies in how to efficiently manage large volumes of data obtained as long-term sequences of high-resolution images. A promising approach is known as image foveation, which is able to reduce the computational resources used (i.e., memory storage) in several applications. In this paper, we propose an image foveation approach towards plant phenology tracking where relevant changes within an image time series guide the creation of foveal models used to resample unseen images. By doing so, images are taken to a space-variant domain where regions vary in resolution according to their contextual relevance for the application. We performed our validation on a dataset of vegetation image sequences previously used in plant phenology studies.

Keywords
foveal model; image foveation; hilbert curve; plant phenology tracking; space-variant image

Journal
Remote Sensing: Volume 12, Issue 9

People

Dr Thiago Silva

Senior Lecturer, Biological and Environmental Sciences