This course will introduce the student to the IDL environment as a data visualization tool and a programming language. The student will learn the various capabilities of the package and how they can rapidly prototype solutions to various science and engineering problems. As these solutions are developed, fundamental concepts of programming and data structures will be introduced. Programming assignments will include fundamental imaging related problems and will work with scalar, vector and array processes. This course will emphasize the need for concrete problem definition, problem decomposition into smaller sub-problems, implementation/testing, and presentation/documentation of the algorithms and results. (Algebra and trigonometry) Class 4, Credit 4 (PDF)

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, geometrical operations for scale and rotation, and grey-level resampling techniques. The student will be introduced to the computation of the discrete and fast Fourier transforms for one- and two-dimensional functions and the techniques of frequency domain filtering. Emphasis is placed on applications and efficient algorithmic implementation using the IDL programming language. (1016-305, 1051-211 or equivalent) Class 4, Credit 4 (PDF)

This course is an introduction to the more advanced concepts of digital image processing. The student will be exposed to image reconstruction, noise sources and techniques for noise removal, information theory, image compression, video compression, wavelet transformations and the basics of digital image watermarking. Emphasis is placed on applications and efficient algorithmic implementation using the IDL programming language. (1051-461) Class 4, Credit 4 (PDF)

This course discusses the digital image processing concepts and algorithms used for the analysis of hyperspectral, multispectral and multi-channel data in remote sensing and other application areas. Concepts are covered at the theoretical and implementation level using current, popular commercial software packages and high-level programming languages for examples, homework and programming assignments. The requisite multivariate statistics will be presented as part of this course as an extension of the univariate statistics that the students have previously been exposed to. Topics to be covered will include methods for supervised data classification, clustering algorithms and unsupervised classification, multispectral data transformations, data redundancy reduction techniques, image-to-image rectification, and data fusion for resolution enhancement. (1051-211 or equivalent, 1016-351, 1061-352) Class 4, Credit 4 (PDF)

Guidance for undergraduate level research projects leading to Bachelor of Science degree in Imaging Science. I am currently serving on or have served as the primary advisor for the following students:

Current

1. Russell Barkley (co-advisor with Risa Robinson) (BS)

Completed

1. Michael Denning (co-advisor with Joel Kastner) / February 2007 / Classification of astronomical infrared sources using Spitzer space telescope data (PDF)
2. Brandon Migdal / May 2004 / Extraction methods of watermarks from linearly-distorted images to maximize signal-to-noise ratio (PDF)
3. Seth Weith-Glushko / May 2004 / Automatic tie-point generation for oblique aerial imagery: An algorithm (PDF)
4. Christopher Bayer / May 2005 / Development of algorithm for fusion of hyperspectral and multispectral imagery with the objective of improving spatial resolution while retaining spectral data (PDF)
5. Bethany Choate / May 2006 / OPTED OUT
6. William Pfeister / May 2006 / OPTED OUT

The Multidisciplinary Senior Design program prepares students for modern engineering practice through a multidisciplinary, team-based design experience in which the students apply the skills and knowledge acquired in earlier coursework to define, analyze, design and implement solutions to unstructured, open-ended, multidisciplinary engineering problems while adhering to customer requirements and recognized engineering standards. The projects are sponsored by wide range of industries and government organizations. I am currently serving on or have served as the primary advisor for the following students:

Current

NONE

Completed

1. Rick Andol, Kathryn Berens, William Casolara, Matthew Harris, Robert Jaromin, Ross Strebig / 20062,20063 / P07521 BRDF Imaging Platform

This course emphasizes the algorithm development and implementation of advanced digital imaging applications. Modular programming concepts are emphasized along with good coding and documentation practices. The course will be carried out in the UNIX operating environment and IDL will be the programming language utilized. Language specific characteristics such as the use of IDL widgets for graphical user interface development, the use of IDL objects, the use of ENVI specific functions and procedures, further treatment of image data types, and color management will be explored. Example algorithmic areas that may be explored are image compression, color space transformations, frequency domain image reconstruction, and the use of multi-band imagery. (1051-211 or permission of instructor) Class 2, Credit 2

This course is intended to develop the students skills in applied computing and research techniques. A prerequisite to scientific advancement is a thorough understanding of historical and recent literature relevant to the field of study. This often involves repeating experiments that predecessors and current colleagues have performed. Often, insights are gained when experiments are repeated that cannot be realized simply by reading an article in a professional journal or conference proceeding. In this course, the student will choose an article from the historical or recent literature that describes a computational technique used in the field of imaging science. The student will implement the described algorithm in the computer language of their choice, and attempt to repeat the results obtained by the author. Along the way, the student will make three oral presentations during class, the first describing the referenced research, the second, a report on their progress in re-implementing the referenced work, and the third, describing the success, failure or questions that arose during execution of the project. The intent is to develop a critical approach to reading published research, questioning both implementation and results in order to gain a thorough understanding of the work. (1051-211 or equivalent and permission of the instructor) Class 2, Credit 3 (PDF)

An immersion in the instrumentation used by the remote sensing community to collect imagery as well as ground truth data. Conducted as a hands-on project, the students will plan a campaign, orchestrate and/or execute the aircraft or satellite collection, be on the ground during overflight to collect relevant truth data using field instrumentation, and finally perform a comparison of the results from data analysis to the known truth. (1017-431 or equivalent, 1051-463, 1051-401 and permission of instructor) Class 3, Lab 3, Credit 4

A study to determine whether agglomerative hierarchical clustering used as a pre-cursor to traditional K-mean unsupervised classification as a means of determining the initial cluster mean values provides better selection than the traditional random choice methodology. (Bethany Choate)

An implementation of the seam carving algorithm for dynamic image resizing was undertaken in the IDL programming language to identify any limitations that may be present and demonstrate the viability of this technique. (Jarret Whetstone)

This course will provide the basic fundamentals necessary to understand the field of remote sensing including sensors designs, photogrammetry, radiation propagation, atmospheric compensation, unique image processing techniques, multispectral concepts and techniques, and image/information combining methodologies. Class 3, Lab 1, Credit 4

This course will provide the basic understanding of imaging systems, image transformation and associated mathematics and computational processes needed for upper-level classes in the imaging science graduate program. Topics covered include linear vector spaces, image mathematics, image statistics and point processing, linear and nonlinear image filters, image transforms and computer algorithms. Computational methods and techniques for essential processes for imaging systems are used as the course framework. Class 4, Credit 4

A study in sensor design specifications was carried out to prepare sensor models for the Digital Image and Remote Sensing laboratories Synthetic Image Generation model (DIRSIG). The student performed a very thorough review of the literature to establish a comprehensive database of sensor characteristics for systems in use today by commercial and government organizations. (Cynthia Scigaj)

A study to establish the theoretical framework necessary to understand BRDF in the visible to near infrared (VNIR) spectral region was conducteded, along with BRDF measurement techniques. Some popular BRDF models, which enable interpolation of measured data are reviewed. The most general form of the BRDF, that which included polarization, was examined in detail. A viable polarimetric BRDF measurement technique was presented, along with models which may be used to extrapolate the measured data. Potential applications of spectropolarimetric BRDF to remote sensing was reviewed. Finally, a recommendation was made for a simple outdoor BRDF measurement system which enables the application of spatial resolution-dependent BRDF variation toward hyperspectral algorithms and synthetic image generation. (James Shell)

A study to establish the utility of polarization imagery collected with the LIAS WASP-lite sensor. This work included a system design/performance trade-off of off-the-shelf polarization filters for incorporation in the WASP-lite build being carried out concurrently. In addition, processing algorithms were developed to exploit the future imagery. (Michael Foster)

A study to identify and implement numerous mathematical models of bidirectional reflectance functions was carried out. In this study the Priest-Germer, Torrance-Sparrow, Beard-Maxwell, and Ward models were described and implemented in a Matlab based simulation environment. (Matt Montanaro)

A self-directed study in object-oriented programming using the C++ programming language for image processing and medical imaging system modeling was undertaken. (Sang-Yun Moon)

An introduction to object-oriented programming in C++ with the purpose of understanding the numerical radiometric modeling in DIRSIG's photon mapping radiometry solver. (Jacqueline Spier)

The radiometric and geometric calibration of a constructed image-based spectral gonioradiometer was undertaken. Topics investigated include lamp spectral power distribution, lamp stability, geometric positioning, spectrometer alignment, spectrometer response function, and spectrometer stability. The final product is a LabView control system allowing for calibrated output of spectral bidirectional reflectance factors for sample materials. (May Arsenovic)

Guidance for graduate level research projects leading to an online Master of Science degree in Imaging Science. I am currently serving on or have served as a primary advisor for the following students:

Current

1. Cindy Scigaj (MS)

Completed

1. Timothy Grabowski (MS) / May 2006 / Effects of pixel size on apparent emissivity signatures of materials with longwave infrared spectral characteristics (PDF)
2. Gregory Gosian (MS) / February 2006 / A non-probabilistic, compact compression algorithm suitable for deep space solar system mission image transmission (PDF)

Guidance for graduate level research projects leading to Master of Science or Doctor of Philosophy degrees in Imaging Science. I am currently serving on or have served as a primary advisor* or committee member for the following students:

Current

1. May Arsenovic (Ph.D.)*
2. Chabitha Devaraj (MS)
3. Feng Li (Ph.D.)
4. Matthew Montanaro (Ph.D.)*
5. Philip Nau (MS/Environmental Science)
6. Frank Padula (MS)
7. Ariel Schlamm (Ph.D.)
8. Alvin Spivey (Ph.D.)
9. Don Taylor (MS)

Completed

1. John Francis (MS) / May 1989 / Pixel-by-pixel reduction of atmospheric haze effects in multispectral digital imagery of water
2. Denis Robert (MS) / May 1989 / Selection and analysis of optimal textural features for accurate classification of monochrome digitized image data
3. Jan North (MS) / December 1989 / Fourier image synthesis and slope spectrum analysis of deep water, wind-wave scenes viewed at Brewster's angle
4. Wendy Rosenblum (MS) / May 1990 / Optimal selection of textural and spectral features for scene segmentation
5. Curtis Munechika (MS) / August 1990 / Merging panchromatic and multispectral images for enhanced image analysis
6. Eric Shor (MS) / May 1990 / 3-D longwave infrared synthetic scene simulation
7. Jonathan Wright (MS) / May 1991 / Evaluation of LOWTRAN and MODTRAN for use over high zenith angle/long path length viewing
8. Gustav Braun (MS) / July 1992 / Quantitative evaluation of six multispectral, multiresolution image merger routines
9. Robert Merisko (MS) / July 1992 / Enhancement to atmospheric-correction techniques for multiple thermal images
10. David Ehrhard (MS) / September 1992 / Application of Fourier-based features for classification of synthetic aperture radar imagery
11. Sharon Cady (MS) / April 1992 / Multi-scene atmospheric normalization of airborne imagery: Application to the remote measurement of lake acidification
12. Donna Rankin (MS) / February 1993 / Validation of DIRSIG an infrared synthetic scene generation model
13. Adam Hanson (MS) / June 1993 / Character recognition of optically blurred textual images using moment invariants
14. Kaleen Moriarty (MS)* / August 1993 / Automated image-to-image rectification for use in change detection analysis as applied to forest clearcut mapping
15. Richard Stark (MS) / September 1993 / Synthetic image generator model: Application of specular and diffuse reflectivity components and performance evaluation in the visible region
16. Gary Ralph (MS) / June 1994 / Characterization of the radiometric performance of an IR scene projector
17. Elizabeth Frey (MS)* / July 1995 / An examination of distributional assumptions in Landsat TM imagery
18. Neil Scanlan (MS) / August 2003 / Comparative performance analysis of texture characterization models in DIRSIG (PDF)
19. Erin Peterson (MS) / August 2004 / Synthetic landmine scene development and validation in DIRSIG (PDF) (SPIE 2004)
20. Kris Barcomb (MS) / August 2004 / High-resolution, slant-angle scene generation and validation of concealed targets in DIRSIG (PDF) (SPIE 2004)
21. Marianne Lipps (MS) / August 2004 / Task influence of scene content selected by active vision (PDF)
22. Susan Hojnacki (Ph.D.) / May 2005 / A source classification algorithm for astronomical X-ray imagery of stellar clusters (PDF)
23. Erin O'Donnell (MS)* / August 2005 / Detection and identification of effluent gases using invariant hyperspectral algorithms (PDF) (SPIE 2004) (SPIE 2005)
24. Melissa Hofer (MS/Computer Science) / August 2005 / A website and corresponding database to support the Digital Imaging and Remote Sensing (DIRS) lab in the Chester F. Carlson Center for Imaging Science at the Rochester Institute of Technology (PDF)
25. David Pogorzola (MS)* / October 2005 / Gas plume species identification in LWIR hyperspectral imagery by regression analyses (PDF)
26. James Shell (Ph.D.) / November 2005 / Polarimetric remote sensing in the visible to near infrared (PDF)
27. Timothy Hattenberger (MS) / March 2006 / A psychovisual investigation of global illumination algorithms used in augmented reality (PDF)
28. Kristin Strackerjan (MS) / July 2006 / Modelling the spectral effects of water and soil as surface contaminants in a high resolution optical image simulation (PDF)
29. Brian Dobbs (MS) / October 2006 / The incorporation of atmospheric variability into DIRSIG (PDF)
30. Seth Weith-Glushko (MS)* / February 2007 / Quantitative analysis of infrared contrast enhancement algorithms (PDF)
31. Michael Gartley (Ph.D.) / April 2007 / Polarimetric modeling of remotely sensed scenes in the thermal infrared (PDF)
32. Yan Li (Ph.D.) / July 2007 / An integrated water quality modeling system with dynamic remote sensing feedback (PDF)
33. Brent Bartlett (Ph.D.) / August 2007 / Improvement of retrieved reflectance in the presence of clouds (PDF)
34. Michael Foster (Ph.D.) / August 2007 / Using LIDAR to geometrically constrain signature spaces for physics-based target detection (PDF)
35. Zhen Wang (Ph.D.) / August 2007 / Modeling wildland fire radiance in synthetic remote sensing scenes (PDF)
36. Marvin Boonmee (Ph.D.) / October 2007 / Land surface temperature and emissivity retrieval from thermal infrared hyperspectral imagery (PDF)
37. Derek Walvoord (Ph.D.) / May 2008 / Advanced correlation-based character recognition applied to the Archimedes palimpsest (PDF)
38. Marcus Stefanou (Ph.D.) / July 2008 / Spectral image utility for target detection applications (PDF)

C Programming for Imaging Science (RIT)
C++ Programming for Imaging Science (RIT)
FORTRAN Programming (RIT)
Programming Concepts for Technical Photography (RIT)
Digital Image Processing: Image Compression (RIT)
Principles of Remote Sensing Image Analysis: Radiometry (RIT)
Principles of Remote Sensing Image Analysis: Multispectral Image Analysis (RIT)
Principles of Remote Sensing Image Analysis: Thermal Infrared Remote Sensing (RIT)
Digital Image Processing with Application to Remote Sensing (Royal Canadian Air Force)
Special Topics in Imagery Analysis (NIMA College)