A Lightweight Double Compression Detector for HEIF Images Based on Encoding Information

Alessandro Piva is currently an Associate Professor at the Department of Information Engineering at the University of Florence. He is also the Head of the FORLAB, the Multimedia Forensics Laboratory, and the University of Florence. His research interests include information forensics and security and image and video processing. In the first topic, he is interested in data hiding, signal processing in the encrypted domain, and image and video forensic techniques. In the second area, he is interested in the design of image and video processing and analysis techniques for cultural heritage, medical, and industrial applications. In the above research topics, he is the co-author of more than 60 articles published in international journals and 130 papers published in international conference proceedings.

Giovanni Ramponi has been a Full Professor of Electronics at the Department of Engineering and Architecture, University of Trieste, Italy, since 2000. He received a degree in Electronic Engineering in 1981. He was a member of the Board of Doctoral Studies in Industrial and Information Engineering from 1993 to 2021. From 2017 to 2021, he was the coordinator of studies for the Laurea degree in Electronic and Computer Engineering. From 2018 to 2021, he was a Member of the Academic Senate at UniTS. He is/has been an Associate Editor of IEEE Signal Processing Letters, IEEE Transactions on Image Processing, and the SPIE Journal of Electronic Imaging. He was Chairman of the Technical Programme of IEEE and EURASIP symposia. He has been locally responsible for, or has participated in, various scientific activities with contracts at EU level (CHIRON Artemis Joint Undertaking, SCHEMA Network of Excellence, COST 276 and 254 projects, LTR and ESPRIT contracts, TMR project), at national level (CNR, MIUR PRIN, MIUR FIRB) and local level. He has regularly been a member of the technical committee of international conferences. His research interests include nonlinear digital signal processing, enhancement and feature extraction in images and image sequences, image visualization, image quality evaluation, and deep learning techniques for image processing.