Prof. Dr. Cosimo Distante
CNR - ISASI
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Academic Career Length
29Years (1998-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 August 2018 in Light: Science & Applications
Journal Article
VBVittorio Bianco
Vittorio BiancoPMPasquale Memmolo
Pasquale Memmolo
Marco LeoSMSilvio Montresor
Silvio Montresor
Cosimo DistantePFPietro Ferraro
Pietro Ferraro +3
Digital holography (DH) has emerged as one of the most effective coherent imaging technologies. The technological developments of digital sensors and optical elements have made DH the primary approach in several research fields, from quantitative phase imaging to optical metrology and 3D display technologies, to name a few. Like many other digital imaging techniques, DH must cope with the issue of speckle artifacts, due to the coherent nature of the required light sources. Despite the complexity of the recently proposed de-speckling methods, many have not yet attained the required level of effectiveness. That is, a universal denoising strategy for completely suppressing holographic noise has not yet been established. Thus the removal of speckle noise from holographic images represents a bottleneck for the entire optics and photonics scientific community. This review article provides a broad discussion about the noise issue in DH, with the aim of covering the best-performing noise reduction approaches that have been proposed so far. Quantitative comparisons among these approaches will be presented.
13 May 2011 in Optics Letters
Journal Article
PMPasquale Memmolo
Pasquale MemmoloCosimo DistanteMPM. Paturzo
M. Paturzo
AFA. Finizio
A. Finizio
PFPietro Ferraro
Pietro FerraroBJB. Javidi
B. Javidi
The searching and recovering of the correct reconstruction distance in digital holography (DH) can be a cumbersome and subjective procedure. Here we report on an algorithm for automatically estimating the in-focus image and recovering the correct reconstruction distance for speckle holograms. We have tested the approach in determining the reconstruction distances of stretched digital holograms. Stretching a hologram with a variable elongation parameter makes it possible to change the in-focus distance of the reconstructed image. In this way, the proposed algorithm can be verified at different distances by dispensing the recording of different holograms. Experimental results are shown with the aim of demonstrating the usefulness of the proposed method, and a comparative analysis has been performed with respect to other existing algorithms developed for DH.
30 March 2024 in ISPRS Open Journal of Photogrammetry and Remote Sensing
Journal Article
MGMohamed Fadhlallah Guerri
Mohamed Fadhlallah GuerriCosimo Distante
Paolo SpagnoloFBFares Bougourzi
Fares BougourziATAbdelmalik Taleb-Ahmed
Abdelmalik Taleb-Ahmed
10 December 2019 in Advanced Intelligent Systems
Journal Article
VBVittorio Bianco
Vittorio BiancoPMPasquale Memmolo
Pasquale Memmolo
PCPierluigi Carcagnì
Pierluigi Carcagnì
FMFrancesco Merola
Francesco Merola
MPMelania Paturzo
Melania Paturzo
PFPietro Ferraro
Pietro Ferraro +1
Microplastics (MPs) are a major environmental concern due to their possible impact on water pollution, wildlife, and the food chain. Reliable, rapid, and high‐throughput screening of MPs from other components of a water sample after sieving and/or digestion is still a highly desirable goal to avoid cumbersome visual analysis by expert users under the optical microscope. Here, a new approach is presented that combines 3D coherent imaging with machine learning (ML) to achieve accurate and automatic detection of MPs in filtered water samples in a wide range at microscale. The water pretreatment process eliminates sediments and aggregates that fall out of the analyzed range. However, it is still necessary to clearly distinguish MPs from marine microalgae. Here, it is shown that, by defining a novel set of distinctive “holographic features,” it is possible to accurately identify MPs within the defined analysis range. The process is specifically tailored for characterizing the MPs' “holographic signatures,” thus boosting the classification performance and reaching accuracy higher than 99% in classifying thousands of items. The ML approach in conjunction with holographic coherent imaging is able to identify MPs independently from their morphology, size, and different types of plastic materials.
1 April 2007 in Pattern Recognition
Journal Article
Alessandro LeoneCosimo Distante1 December 2002 in Sensors and Actuators B: Chemical
Journal Article
Cosimo DistanteMarco Leo
Pietro Siciliano
Krishna PersaudAbout Me
Cosimo Distante received an M.S. degree in Computer Science from the University of Bari and a Ph.D. in Materials Engineering from the University of Salento. His main expertise is in the fields of artificial intelligence, computer vision, pattern recognition, and robotics. He has been a visiting scholar at the University of Massachusetts (Amherst, MA), where he carried out research activities on robotics, artificial neural networks, and vision. He joined the faculty of the University of Massachusetts as a Teaching Assistant for the "Artificial Intelligence" course in 1998. He joined CNR in 2001 and has been awarded several fellowships, including the CNR-NATO fellowship. Since 2003, he has been a contract professor for Computer Vision, Pattern Recognition, and Image Processing at the University of Salento. In 2010, he established the "Taggalo" startup. In 2011, he was awarded the National Innovation Prize, Working Capital PNI-Cube Telecom Italia. In 2012, he received the “Premio dei Premi” award for innovation from the Italian Prime Minister. He won the Cisco-Intel ChallengUP in 2015. He was the general chair of ICIAP 2021, IEEE AVSS 2017 and 2021, and ACIVS 2016. He coordinates two joint research labs between CNR and SMEs for security and health technology. He is the unit manager of the CNR Institute of Applied Sciences and Intelligent Systems. He is an expert member in innovation for the Ministry of University and Research and the Ministry of Enterprises and Made in Italy.