Program Overview

Imaging Science Master of Science Degree

Overview

The Imaging Science MS program at RIT provides training and research opportunities in imaging systems used in remote sensing, environmental science, and beyond. The program is geared toward advancing and broadening the skills of professionals working and researching in industries where various imaging modalities are used to research and solve problems in engineering and science.

Careers and Experiential Learning

• Typical Job Titles:
  • Satellite Applications and Research Scientist
  • Machine Learning/Deep Learning Engineer
  • Research Programmer
  • System Engineer
  • Image Scientist
  • Camera Component Engineer
• Cooperative Education: RIT science and math education includes cooperative education and internship experiences in industry and health care settings, as well as research in an academic, industry, or national lab.
• National Labs Career Events and Recruiting: The Office of Career Services and Cooperative Education offers National Labs and federally-funded Research Centers from all research areas and sponsoring agencies a variety of options to connect with and recruit students.

Curriculum

Imaging Science (thesis option), MS degree, typical course sequence

• First Year
  • IMGS-606: Graduate Seminar I
  • IMGS-607: Graduate Seminar II
  • IMGS-617: Image Processing and Discrete Fourier Methods
  • Choose three of the following:
    • IMGS-619: Radiometry
    • IMGS-620: The Human Visual System
    • IMGS-613: Noise and System Modeling
    • IMGS-621: Computer Vision
    • IMGS-633: Optics for Imaging
  • IMGS-790: Research and Thesis
  • IMGS Elective
• Second Year
  • IMGS-790: Research & Thesis
  • IMGS Elective
  • Choose between the following:
    • IMGS-790: Research & Thesis
    • IMGS Electives

Imaging Science (project option), MS degree, typical course sequence

• First Year
  • IMGS-617: Image Processing and Discrete Fourier Methods
  • Choose two of the following:
    • IMGS-619: Radiometry
    • IMGS-620: The Human Visual System
    • IMGS-613: Probability, Noise, and System Modeling
    • IMGS-633: Optics for Imaging
    • IMGS-621: Computer Vision
  • IMGS Elective
• Second Year
  • IMGS-740: Imaging Science MS Systems Project Paper
  • IMGS Electives

Electives

• ASTP-613: Astronomical Observational Techniques and Instrumentation
• CLRS-601: Principles of Color Science
• CLRS-602: Color Physics and Applications
• CLRS-720: Computational Vision Science
• CLRS-820: Modeling Visual Perception
• CSCI-603: Computational Problem Solving
• CSCI-630: Foundations of Artificial Intelligence
• CSCI-631: Foundations of Computer Vision
• EEEE-780: Digital Video Processing
• ENVS-650: Hydrologic Applications of Geographic Information Systems
• IMGS-606: Graduate Seminar I
• IMGS-607: Graduate Seminar II
• IMGS-609: Graduate Laboratory I
• IMGS-613: Noise and System Modeling
• IMGS-617: Image Processing and Discrete Fourier Methods
• IMGS-619: Radiometry
• IMGS-620: The Human Visual System
• IMGS-621: Computer Vision
• IMGS-622: Vision Sciences Seminar
• IMGS-624: Interactive Virtual Env
• IMGS-628: Design and Fabrication of Solid State Cameras
• IMGS-632: Advanced Environmental Applications of Remote Sensing
• IMGS-633: Optics for Imaging
• IMGS-635: Optical System Design and Analysis
• IMGS-639: Principles of Solid State Imaging Arrays
• IMGS-640: Remote Sensing Systems and Image Analysis
• IMGS-642: Testing of Focal Plane Arrays
• IMGS-643: Mathematical Methods of Imaging Science I
• IMGS-644: Mathematical Methods of Imaging Science II
• IMGS-684: Deep Learning for Vision
• IMGS-689: Graduate Special Topics
• IMGS-699: Imaging Science Graduate Co-op
• IMGS-712: Multi-view Imaging
• IMGS-719: Radiative Transfer I
• IMGS-720: Radiative Transfer II
• IMGS-723: Remote Sensing: Spectral Image Analysis
• IMGS-724: Introduction to Electron Microscopy
• IMGS-730: Magnetic Resonance Imaging
• IMGS-732: Synthetic Aperture Radar Image Formation Processing
• IMGS-740: Imaging Science MS Systems Project Paper
• IMGS-765: Performance Modeling and Characterization of Remote Sensing System
• IMGS-766: Geometric Optics and Lens Design
• IMGS-789: Graduate Special Topics: Machine Learning for Difficult Data
• IMGS-790: Research & Thesis
• IMGS-799: Imaging Science Independent Study
• IMGS-830: Advanced Topics in Remote Sensing
• IMGS-890: Research & Thesis
• MATH-605: Stochastic Processes
• MATH-645: Graph Theory
• MCSE-712: Nonlinear Optics
• MCSE-713: Lasers
• MCSE-731: Integrated Optical Devices & Systems
• STAT-641: Applied Linear Models - Regression
• STAT-758: Multivariate Statistics for Imaging Science

Admissions and Financial Aid

• On Campus
  • Offered: Full-time
  • Admit Term(s): Fall or Spring
  • Application Deadline: Fall - January 15 priority deadline, rolling thereafter; Spring - rolling
  • STEM Designated: Yes
• Online
  • Offered: Part-time
  • Admit Term(s): Fall or Spring
  • Application Deadline: Rolling
  • STEM Designated: No
• Application Details
  • Complete an online graduate application
  • Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned
  • Hold a baccalaureate degree (or US equivalent) from an accredited university or college
  • Satisfy prerequisite requirements and/or complete bridge courses prior to starting program coursework
  • Submit a current resume or curriculum vitae
  • Submit a personal statement of educational objectives
  • Submit two letters of recommendation
  • Entrance exam requirements: GRE optional but recommended
  • Submit English language test scores (TOEFL, IELTS, PTE Academic), if required
• Cost and Financial Aid
  • Graduate tuition varies by degree, the number of credits taken per semester, and delivery method
  • View the general cost of attendance or estimate the cost of your graduate degree
  • A combination of sources can help fund your graduate degree
  • Learn how to fund your degree

Faculty

• Jie Qiao: Associate Professor
• Anthony Vodacek: Professor
• Jan van Aardt: Director of Carlson Center for Imaging Science
• All Program Faculty

Research

• The College of Science consistently receives research grant awards from organizations that include the National Science Foundation, National Institutes of Health, and NASA
• The Chester F. Carlson Center for Imaging Science is a unique, interdisciplinary academic unit bringing together the fields of physics, mathematics, engineering, and computer science in the development of new imaging systems and their applications across a wide range of disciplines
• The Imaging Science graduate program has over 100 students doing research on topics such as computer vision, astronomical imaging, satellite-based imaging systems and applications, virtual and augmented reality, and the use of UAVs in precision agriculture
• Students are supported by 18 core program faculty in the Center and another 15+ affiliated faculty members across RIT
• Faculty from the Center conduct research on a broad variety of topics including astronomy, cultural heritage imaging, detectors and imaging systems, human and computer vision, remote sensing, nanoimaging, magnetic resonance, and optical imaging

Events

• Imaging Science Thesis Defense: Macroscopic Roughness Modeling of Satellite Multi-Layer Insulation Reflectance

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Contact

• Admissions Contact: Lindsay Lewis, Senior Assistant Director, Office of Graduate and Part-Time Enrollment Services, Enrollment Management, 585-475-5532
• Program Contact: Anthony Vodacek, Professor, Chester F. Carlson Center for Imaging Science, College of Science, 585-475-7816