An innovative degree combining math, physics, engineering, and computer science
Innovative Freshman Experience: No textbooks, no lectures, no homework. Instead, gain hands-on experience designing and building an imaging system for a real-world application in your first year.
Active research laboratories focus on remote sensing, human visual systems, multi-wavelength astronomy, computer and machine vision, cultural heritage imaging, and optics and photonics.
Recent graduates employed at L3Harris, GoPro, Dolby, Facebook Reality Labs, Lockheed Martin, Boeing, Integrated Defense and Security Solution Holdings Inc., EagleView Technologies, and Planetary Resources, Inc.
Join the Imaging Science Club: Network with faculty, staff, and graduate students in imaging science, learn from industry leaders at weekly presentations, and participate in fun, team building activities like the annual Imaging Scavenger Hunt.
$7M in research grants awarded in 2019‑2020.
Augmented and virtual reality. Drones. Satellite imaging. Artificial intelligence and computer vision. Advanced security systems.
This is imaging science.
Imaging science is an extraordinary major that combines physics, math, computer science, and engineering to create fully functioning imaging systems, which are used in everything from scientific research and discovery, satellite imaging, filmmaking, search and rescue, national security, land surveying, AR/VR, and so much more.
What is an Imaging System?
Imaging systems answer fundamental scientific questions, monitor and protect our environment, help keep our nation secure, and aid medical researchers in their quest to conquer disease.
Imaging science is the study of the science, computing, and engineering theories behind the technology that goes into creating images, the integration of this technology into imaging systems, and the application of those systems to gather information and solve scientific problems. Imaging science is used to design and develop cutting-edge imaging systems, such as portable eye trackers, virtual reality devices, satellite systems, digital cameras, or anything that involves recording, processing, displaying, or analyzing image data. As the only university in the country with a bachelor of science in imaging sciences, RIT prepares you for a career in imaging science by immersing you in in-depth course work in imaging, optics, imaging processing, computer vision, imaging detectors, and more. You’ll gain hands-on experience in cutting-edge labs and through course projects on day one, and build upon these experiences throughout your academic career.
Imaging Science Curriculum
The curriculum in the imaging science degree includes the study of:
the physical observables associated with the subject of an image, such as reflected or emitted electromagnetic radiation;
how those observables are captured by devices using optics and detectors such as satellites, digital cameras, medical imaging devices, and astronomical observatories;
how the captured observables are processed using computers and specialized software;
how processed signals are converted into images displayed on paper and electronic devices, and perceived by humans; and
how image quality is assessed and scientific information is extracted.
The imaging science degree begins with Innovative Freshman Experience, a. year-long project-based class in which you'll learn about imaging science while designing and implementing a novel imaging system. As you progress in course work, both theoretical studies and practical application of technologies are reinforced through hands-on laboratory experiments. The curriculum culminates with Imaging Science Senior Project I and II, a two semester, two-course independent research project conducted by you under the guidance of faculty from the Chester F. Carlson Center for Imaging Science. You’ll examine a problem in one of several imaging applications such as remote sensing, astronomy, computer vision, manuscript imaging and enhancement, optics, color science, image quality, or visual perception.
National Labs Career Fair
Hosted by RIT’s Office of Career Services and Cooperative Education, the National Labs Career Fair is an annual event that brings representatives to campus from the United States’ federally funded research and development labs. These national labs focus on scientific discovery, clean energy development, national security, technology advancements, and more. You are invited to attend the career fair to network with lab professionals, learn about opportunities, and interview for imaging science jobs, which range from co-ops and internships to research positions and full-time employment.
Accepted Student Virtual Open House
Get to to know the place where you’ll find your fit and form your future.
What makes an RIT science and math education exceptional? It’s the ability to complete science and math co-ops and gain real-world experience that sets you apart. Co-ops in the College of Science include cooperative education and internship experiences in industry and health care settings, as well as research in an academic, industry, or national lab. These are not only possible at RIT, but passionately encouraged.
Cooperative education, or co-op for short, is full-time, paid work experience in your field of study. And it sets RIT graduates apart from their competitors. It’s exposure–early and often–to a variety of professional work environments, career paths, and industries. RIT co-op is designed for your success.
In the imaging science degree, co-op is optional, but strongly encouraged. Imaging science students gain career experience in a range of industries, including aviation, aerospace, environmental services, medical imaging, national research labs, and more. A sampling of companies that seek out RIT’s imaging science students for co-ops and full-time employment include Adobe, Amazon, Apple, Boeing, Google, L3 Harris, Lockheed Martin, Microsoft, NASA, National Geospatial Intelligence Agency, Naval Undersea Warfare Center, Sandia National Labs, and more.
Professor Carl Salvaggio has been leading many of the UAS (Unmanned Aerial Systems) activities, including the development of flight planning software to acquire imagery from drones using unique flight...
Innovative Freshman Experience I is the first of a two-course sequence. Through the exploration of concepts in physics, math, and computer science, students will experience the creation of a system to address a contemporary technological need through the application of the principles of the scientific method. With the help of faculty and staff from different departments across campus, as well as external experts, students will plan and organize the effort, review current literature applicable to the posed technical challenge, apply hypotheses to address presented scientific questions, conduct experiments to assess technology options, integrate components to create a prototype, and confirm that the prototype and methods meet desired levels of performance. The students will develop a working knowledge of the scientific method and an appreciation for the value of teamwork in technical disciplines, develop the skills required to execute a large project, and increase proficiency in oral and written technical communication. (Academic Level 1, Degree Seeking students.) Lec/Lab 3 (Fall).
Innovative Freshman Experience II
This is the second of a two-course sequence aimed at designing, developing, and building a functional imaging system that will be useful to a real world external constituency to achieve its technical goals. With help from faculty and staff from imaging science and other departments across campus, the unified team of students will plan and organize the effort, assess technology options, integrate components, and confirm that the system meets desired levels of performance. Students will develop a general understanding of the foundational concepts of imaging science, a working knowledge of the principles of systems engineering, an appreciation for the value of teamwork in technical disciplines and practice oral and written technical communication. In this second course of the sequence, students proceed with construction and testing of their system that was designed in IMGS-181. (Prerequisites: MATH-171 or MATH-181 or equivalent course.
Co-requisites: (MATH-172 or MATH-173 or MATH-182) and (PHYS-211 or PHYS-211A).) Lec/Lab 3 (Spring).
General Education – Elective: Vision & Psychophysics
This course presents an overview of the organization and function of the human visual system and some of the psychophysical techniques used to study visual perception. (Prerequisites: SOFA-103 or equivalent course.) Lecture 3 (Fall).
General Education – Mathematical Perspective A: Project-Based Calculus I
This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisite: A- or better in MATH-111 or A- or better in ((NMTH-260 or NMTH-272 or NMTH-275) and NMTH-220) or a math placement exam score greater than or equal to 70 or department permission to enroll in this class.) Lecture 6 (Fall, Spring, Summer).
General Education – Mathematical Perspective B: Project-Based Calculus II
This is the second in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in (MATH-181 or MATH-173 or 1016-282) or (MATH-171 and MATH-180) or equivalent course(s).) Lecture 6 (Fall, Spring, Summer).
General Education – Natural Science Inquiry Perspective: University Physics I
This is a course in calculus-based physics for science and engineering majors. Topics include kinematics, planar motion, Newton's Laws, gravitation, work and energy, momentum and impulse, conservation laws, systems of particles, rotational motion, static equilibrium, mechanical oscillations and waves, and data presentation/analysis. The course is taught in a workshop format that integrates the material traditionally found in separate lecture and laboratory courses. (Prerequisites: C- or better in MATH-181 or equivalent course. Co-requisites: MATH-182 or equivalent course.) Lec/Lab 6 (Fall, Spring).
General Education – Elective: Introduction to Imaging and Video Systems
This course provides an introductory overview of the basic engineering and scientific principles associated with imaging systems. Topics covered include imaging physics, photographic science, human vision and perception, image capture and display technologies (both analog and digital), and digital image processing. This course is taught using both mathematical and phenomenological presentation and prepares students to proceed with more in-depth investigation of these fields in subsequent imaging science and motion picture science courses. Accompanying laboratory exercises provide hands-on experience with the presented concepts. (Co-requisite: MATH-171 or MATH-181 or MATH-181A or equivalent course.) Lab 3, Lecture 2 (Fall).
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. Lecture 1 (Fall, Spring).
General Education – First-Year Writing (WI)
General Education – Artistic Perspective
General Education – Elective
Introduction to Computing and Control
This hands-on course is an introduction to computer programming, simple electronics, and the control of electronic devices using commercially available, single-board computers (e.g. Raspberry Pi). Emphasis will be placed on utilizing the analog and digital input/output ports available on these single-board computers to control and acquire data from electronic devices like optical detectors, LED sources, and servo-motors. The use of open-source software libraries to assist in the control and real-time acquisition of image data from peripheral imaging devices and cameras will be covered in detail. The student will be introduced to object-oriented programming using Python. Fundamentals of flow control, object types and creation, input/output, and problem-solving approaches such as the use of randomness, divide-and-conquer, Monte Carlo, and search will be examined in detail and applied to scientific, mathematical, and imaging-specific related problems. (This class is restricted to IMGS-BS or DIGCIME-BS Major students.) Lecture 3 (Spring).
Probability and Statistics for Imaging
This course introduces the principles of probability and statistics that are used in imaging science. The first half of the course covers probability distributions for discrete and continuous random variables, expectation, variance, and joint distributions. The second half of the course will consider point estimation, statistical intervals, hypothesis testing, inference, and linear regression. (Prerequisites: MATH-182 or MATH-182A or MATH-173 or equivalent course.) Lecture 3 (Spring).
General Education – Elective: Linear and Fourier Methods for Imaging
This course develops the concepts of complex numbers and linear algebra for describing imaging systems in the frequency domain via the discrete and continuous Fourier transforms. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 4 (Spring).
General Education – Elective: Fundamentals of Color Science
This course will introduce students to the field of Color Science. Students will learn about the physical sources of color, the visual mechanisms that provide our experience of color, and the descriptive systems that have been developed for relating the physical and visual properties. Through hands-on projects, students will learn practical methods for measuring, modeling, and controlling color in digital imaging systems. (Prerequisites: SOFA-103 or equivalent course.) Lecture 3 (Fall).
General Education – Elective: Multivariable and Vector Calculus
This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH-219. (Prerequisite: C- or better MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 4 (Fall, Spring, Summer).
General Education – Scientific Principles Perspective: University Physics II
This course is a continuation of PHYS-211, University Physics I. Topics include electrostatics, Gauss' law, electric field and potential, capacitance, resistance, DC circuits, magnetic field, Ampere's law, inductance, and geometrical and physical optics. The course is taught in a lecture/workshop format that integrates the material traditionally found in separate lecture and laboratory courses. (Prerequisites: (PHYS-211 or PHYS-211A or PHYS-206 or PHYS-216) or (MECE-102, MECE-103 and MECE-205) and (MATH-182 or MATH-172 or MATH-182A) or equivalent courses. Grades of C- or better are required in all prerequisite courses.) Lec/Lab 6 (Fall, Spring).
General Education – Elective: Modern Physics I
This course provides an introductory survey of elementary quantum physics, as well as basic relativistic dynamics. Topics include the photon, wave-particle duality, deBroglie waves, the Bohr model of the atom, the Schrodinger equation and wave mechanics, quantum description of the hydrogen atom, electron spin, and multi-electron atoms. (Prerequisites: PHYS-209 or PHYS-212 or PHYS-217or equivalent course.) Lecture 3 (Fall, Spring, Summer).
General Education – Ethical Perspective
General Education – Global Perspective
This course introduces the concepts of quantitative measurement of electromagnetic energy. The basic radiometric and photometric terms are introduced using calculus-based definitions. Governing equations for source propagation and sensor output are derived. Simple source concepts are reviewed and detector figures of merit are introduced and used in problem solving. The radiometric concepts are then applied to simple imaging systems so that a student could make quantitative measurements with imaging instruments. (Prerequisites: MATH-182 or MATH-182A or MATH-173 and PHYS-212 or equivalent courses.) Lab 3, Lecture 2 (Fall).
This course introduces the analysis and design of optical imaging systems based on the ray model of light. Topics include reflection, refraction, imaging with lenses, stops and pupils, prisms, magnification and optical system design using computer software. (Prerequisites: PHYS-212 or equivalent course.) Lab 3, Lecture 2 (Fall).
Light waves having both amplitude and phase will be described to provide a foundation for understanding key optical phenomena such as interference, diffraction, and propagation. Starting from Maxwell's equations the course advances to the topic of Fourier optics. (Prerequisites: (PHYS-212 and IMGS-261) or (PHYS-283 and PHYS-320) or equivalent courses.) Lab 3, Lecture 2 (Spring).
Interactions Between Light and Matter
This course introduces the principles of how light interacts with matter. The principles of atomic physics as applied to simple atoms are reviewed and extended to multi-electron atoms to interpret their spectra. Molecular structure and spectra are covered in depth, including the principles of lasers. The concepts of statistical physics concepts are introduced and applied to the structure of crystalline solids, their band structure and optical properties. These concepts are then used to understand electronic imaging devices, such as detectors. (Prerequisite: PHYS-213 or equivalent course.) Lecture 3 (Spring).
Image Processing and Computer Vision I
This course is an introduction to the basic concepts of digital image processing. The student will be exposed to image capture and image formation methodologies, sampling and quantization concepts, statistical descriptors and enhancement techniques based upon the image histogram, point processing, neighborhood processing, and global processing techniques based upon kernel operations and discrete convolution as well as the frequency domain equivalents, treatment of noise, geometrical operations for scale and rotation, and grey-level resampling techniques. Emphasis is placed on applications and efficient algorithmic implementation using the student's programming language of choice. (Prerequisites: IMGS-180 and IMGS-261 or equivalent courses.) Lecture 3 (Fall).
Image Processing & Computer Vision II
This course is considers the more advanced concepts of digital image processing. The topics include image reconstruction, noise sources and techniques for noise removal, information theory, image compression, video compression, wavelet transformations, frequency-domain based applications, morphological operations, and modern digital image watermarking and steganography algorithms. Emphasis is placed on applications and efficient algorithmic implementation using the student’s computer programming language of choice, technical presentation, and technical writing. (Prerequisites: IMGS-361 or equivalent course.) Lecture 3 (Spring).
General Education – Social Perspective
General Education – Immersion 1
Imaging Systems Analysis and Modeling
The purpose of this course is to develop an understanding and ability to model signal and noise within the context of imaging systems. A review of the modulation transfer function is followed by a brief review of probability theory. The concept of image noise is then introduced. Next, random processes are considered in both the spatial and frequency domains, with emphasis on the autocorrelation function and power density spectrum. Finally, the principles of random processes are applied to signal and noise transfer in multistage imaging systems. At the completion of the course the student will be able to model signal and noise transfer within a multistage imaging system. (Prerequisites: IMGS-211 and IMGS-261 and IMGS-341 and IMGS-322 or equivalent courses.) Lecture 4 (Fall).
This course provides an overview of the underlying physical concepts, designs, and characteristics of detectors used to sense electromagnetic radiation having wavelengths ranging from as short as X-rays to as long as millimeter radiation. The basic physical concepts common to many standard detector arrays will be reviewed. Some specific examples of detectors to be discussed include photomultipliers, micro channel plates, hybridized infrared arrays, positive-intrinsic-negative (PIN) detectors, and superconductor-insulator-superconductor (SIS) mixers. The use of detectors in fields such as astronomy, high energy physics, medical imaging and digital imaging will be discussed. (Prerequisites: IMGS-251 and IMGS-341 or equivalent courses.) Lecture 3 (Spring).
Imaging Science Senior Project I (WI-PR)
Part of this course is designed to develop skills in technical communication and scientific research practices. Each student is required to research, write, and present a proposal for an independent research project. Students initiate the research project defined in the proposal developed in the course. The project is supervised by a faculty member in imaging science and is expected to require 9-12 hours per week. (This course requires permission of the Instructor to enroll.) Research 3 (Fall, Spring, Summer).
Imaging Science Senior Project II
Students perform the independent research project under the advising of a faculty member in imaging science. The research effort is expected to require 9-12 hours per week. The research outcomes are presented in written and oral form. (Prerequisites: IMGS-502 or equivalent course.) Research 3 (Fall, Spring, Summer).
General Education – Immersion 2, 3
Total Semester Credit Hours
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
For all bachelor’s degree programs, a strong performance in a college preparatory program is expected. Generally, this includes 4 years of English, 3-4 years of mathematics, 2-3 years of science, and 3 years of social studies and/or history.
Specific math and science requirements and other recommendations
3 years of math required; pre-calculus recommended
Transfer course recommendations without associate degree
Courses in math, computer science, liberal arts, and physics
Appropriate associate degree programs for transfer
AS degree in liberal arts with math/science option, computer science, engineering science, science
Faculty, staff, and students conduct research sponsored by both industry and the government. Dedicated research support ensures that you are exposed to the latest developments in the rapidly expanding field of imaging science.
Undergraduate research experiences are available through the Chester F. Carlson Center for Imaging Science and are highly encouraged. The Carlson Center focuses it research initiatives on astronomy, cultural heritage imaging, detectors and imaging systems, human and computer vision, remote sensing, nano-imaging, magnetic resonance, and optical imaging. Research opportunities enable you to immerse yourself in these dynamic areas of study as you engage in the real-world application of the information you are studying in the classroom.
An RIT faculty member is creating new artificial intelligence systems that could empower agricultural researchers, breeders, nurseries, and other users to analyze the roots of their crops with the power of their smartphones. Assistant Professor Guoyu Lu is receiving a $450,000 New Investigator grant from the U.S. Department of Agriculture to conduct the research.
Analytical thinking, complex problem solving, creativity, resiliency, and flexibility are among the top skills needed for emerging careers by 2025. Anticipating these rapid changes in the workplace—further accelerated by lessons learned from the COVID-19 pandemic—RIT is seizing on the opportunity to guide students to “new economy majors” that are multidisciplinary, transformative, and future-focused.