Real-time detection and classification of active regions from solar images using sector-based hashing

Abstract

We present a new approach for real-time retrieval and classification of solar images using a proposed sector-based image hashing technique. To this end, we generate intermediate hand-crafted features from automatically detected active regions in the form of layer-sector-based descriptors. Additionally, we employ a small fully-connected autoencoder to encode and finally obtain the concise Layer-Sector Solar Hash. By reducing the amount of data required to describe the Sun images, we achieve almost real-time retrieval speed of similar images to the query image. Since solar AIA images are not labeled, for the purposes of the presented test experiments, we consider images produced within a short time frame (typically up to several hours) to be similar. This approach has several potential applications, including searching, classifying, and retrieving solar flares, which are of critical importance for many aspects of life on Earth.