A Novel Method for Solar Image Retrieval Based on the Parzen Kernel Estimate of the Function Derivative and Convolutional Autoencoder

The Sun's activity has an enormous impact on the climate and technology on the Earth. The NASA Solar Dynamic Observatory (SDO) spacecraft produces an enormous number of images a day. We propose a technique for fast retrieving and indexing these images. We use image preprocessing, novel edge detection based on a nonparametric Parzen kernel estimator for discovering active regions and a convolutional autoencoder to generate a concise solar image description. Such real-valued hashes can be used to retrieve similar Sun images. Moreover, they can be a basis to classify or predict Solar activity. The experiments showed excellent accuracy and relatively good speed of the proposed method.