Image and Video Processing and Communications Lab (ivPCL)

Featured Publications

Breaking News:

Professor Pattichis will deliver an invited talk titled Large-scale Biomedical Video Analysis for Computer Aided Diagnosis for his EAMBES fellow talk at IEEE BHI 2022.

Professor Marios Pattichis has been elected a 2022 Fellow of the European Alliance of Medical and Biological Engineering and Science (EAMBES) for his contributions to biomedical image analysis.

Professor Marios Pattichis will give a Keynote on Large-scale Video Analysis at the International Conference On Interactive Media, Smart Systems And Emerging Technologies (IMET 2022).

Professor Marios Pattichis is a guest editor to two special issues:
  • “Large scale video analytics for clinical decision support,” IEEE Journal of Biomedical and Health Informatics , to appear in 2022-2023.
  • “Teaching and learning mathematics and computing in multilingual contexts,” Teachers College Record, to appear in 2022.

Recent publications

A. Gomez, M. Pattichis and S. Celedón-Pattichis, Speaker Diarization and Identification from Single Channel Classroom Audio Recordings Using Virtual Microphones , in IEEE Access, doi: 10.1109/ACCESS.2022.3177584.

C. A. LópezLeiva, G. Noriega, S. Celedón-Pattichis, & M. S. Pattichis, From students to cofacilitators: Latinx students’ experiences in mathematics and computer programming , Teachers College Record, 2022.

G. Esakki, A. S. Panayides, V. Jatla, and M. S. Pattichis, Adaptive Video Encoding for Different Video Codecs , in IEEE Access, vol. 9, pp. 68720-68736, 2021, doi: 10.1109/ACCESS.2021.3077313 .

Ulloa, A., Jing, L., Good, C. W., vanMaanen, D. P., Raghunath, S., Suever, J. D., Nevius, C. D., Wehner, G. J., Hartzel, D. N., Leader, J. B., Alsaid, A., Patel, A. A., Kirchner, H. L., Pfeifer, J. M., Carry, B. J., Pattichis, M. S., Haggerty, C. M., Fornwalt, B. K., Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality, in press, Nature BME, published online, 2021.

Kent, Robert B and Pattichis, M.S., "Design, Implementation, and Analysis of High-Speed Single-Stage N-Sorters and N-Filters." , IEEE Access, volume 9, pp. 2576-2591, December 2020.

Silva, R.F., Plis, S., Adali, T., Pattichis, M.S., and Calhoun, V.D., “Multidataset Independent Subspace Analysis with Application to Multimodal Fusion,”,IEEE Transactions On Image Processing, vol. 30, pp. 588-602, October 2020.

Carranza, C., Llamocca, D., Pattichis, M. S., Fast and Scalable 2D Convolutions and Cross-correlations for Processing Image Databases and Videos on CPUs. IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) 2020.

Sanchez Tapia, L., Pattichis, M. S., Celedón-Pattichis, S., & LópezLeiva, C., The Importance of the Instantaneous Phase for Face Detection Using Simple Convolutional Neural Networks. IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) 2020.

Constantinou, K., Constantinou, I., Pattichis, C.S., and Pattichis, M.S., Medical Image Analysis Using AM-FM Models and Methods, in press, IEEE Reviews in Biomedical Engineering, 2020.

Andreas S. Panayides., Pattichis, M.S., Pantziaris, M., Constantinides, A.G., and Pattichis, C.S., The Battle of the Video Codecs in the Healthcare Domain - A Comparative Performance Evaluation Study Leveraging VVC and AV1, IEEE Access, 8, pp.11469-11481, 2020.

Jatla, V., Pattichis, M.S., and Arge, C.N., Image Processing Methods for Coronal Hole Segmentation, Matching, and Map Classification, IEEE Transactions On Image Processing, 29, pp. 1641-1653, 2019.

Battle of the Video Codecs: Coding-Efficient VVC vs. Royalty-Free AV1,
by Rina Diane Caballar, featuring Professor Andreas S. Panayides and our recent IEEE Access paper, Benjamin Bross and Kedar Tatwawadi, in The Tech Alert Newsletterx by IEEE SPECTRUM

Contact Us

Prof. Marios S. Pattichis
Electrical and Computer Engineering
ECE Bldg., Room 229A MSC01 1100
1 University of New Mexico
Albuquerque, NM 87131-0001
P: (505) 277-0486
Fax: (505) 277-8298
Video Activity Recognition

Biomedical image and video processing and Communications

Over the years, the lab has contributed signal and image analysis components of several projects in computer aided diagnosis (CAD). A summary of CAD projects includes: stroke ultrasound image analysis, brain image analysis, hysteroscopic image analysis, eye image analysis, biomedical signal analysis, chest radiograph image analysis, and electron microscopy image analysis.


AM-FM Representations

Multidimensional Amplitude Modulation - Frequency Modulation (AM-FM) representations provide non-stationary representations of image and video content. AM-FM representations capture unique image and video features that can lead to exciting applications in image and video analysis (e.g., in computer aided diagnosis).

Video Activity Recognition

Video Activity Recognition

The AOLME project has demonstrated successful implementation of an integrated curriculum for teaching computing foundations based on middle-school mathematics. Current educational research is focused on the development of learning models to understand how students acquired computing knowledge by participating in the project. Current engineering research is focused on the development of automated video analysis methods to support the development of the learning models.



Advancing Out-of-school Learning in Mathematics and Engineering

This is an interdisciplinary effort -from faculty with areas of expertise in bilingual education, mathematics education (Prof. Sylvia Celedón-Pattichis and Prof. Carlos A. LópezLeiva), and electrical and computer engineering (Prof. Marios Pattichis and Dr. Daniel Llamocca)- designed to support interactive and visual learning in engineering and mathematics of middle school students, especially from underrepresented groups.


Dynamically reconfigurable architectures for image and video processing

By developing hardware architectures for specific signal, image, and video processing operations, it is possible to achieve very high performance while reducing power requirements. There is strong interest in developing efficient architectures for computing fast convolutions and implementing 2D filterbanks for real-time video processing applications. Also refer to the DRASTIC project for related research.



DRASTIC is focused on the development of adaptive video processing systems that can change in response to content, their environment, or user needs. The DRASTIC platform allows changes in both the software and the hardware that is used to process the videos.


Solar and Remote Sensing

Solar image analysis research requires the development of reliable coronal hole segmentation methods that are validated by manual segmentations from at-least two different independent experts. UNM developed the manual segmentation software that was used for validation of automated segmentation methods. UNM senior design teams have and continue working on a WebApp to support manual segmentations from a large number of users. Current research is also focused on developing matching algorithms for driving physical models from accurate coronal hole detection from solar observation images.



We are very interested in finding commercial partners to help commercialize our research. Please do not hesitate to contact us to discuss potential partnerships. We are eager to help!

Technical questions:
  official email:
  phone: (505) 277-0486


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