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1051.211 / Programming for Imaging ScienceView EvaluationsThis 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) 1051.361 / Digital Image Processing IView EvaluationsThis 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) 1051.462 / Digital Image Processing IIView EvaluationsThis 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) 1051.463 / Digital Image Processing IIIView EvaluationsThis 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)
1051.502 / 1051.503 / Senior ProjectGuidance for undergraduate level research projects leading to Bachelor of Science degree in Imaging Science. I am currently serving on or have served as an advisor for the following students:
0303.560 / 0303.561 / Multidisciplinary Engineering Senior DesignThe 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 an advisor for the following students:
1051.553 / Special Topics - Programming for Imaging Science IIView EvaluationsThis 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 1051.553 / Special Topics - Applied Computing for Imaging ScienceView EvaluationsThis 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) 1051.599 / 1055.359 / Undergraduate Independent Study (Honors Research)
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. Completed: February 2002 Bethany Choate (Undergraduate) 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 Completed: May 2005 Jarrett Whetstone (Undergraduate) 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. Completed: November 2007 Erin Schmidtmann (Undergraduate) A study in programming using the IDL language with applications to image and radiometric processing. Completed: May 2008 Ann Nunziata (Undergraduate) A primer class on LabView programming with a specific application to motor and camera control applied to the DIRS laboratory spectrogoniometric brdf measurement system. Completed: August 2008 Jon Purington (Undergraduate) An introduction to Cocoa programming under Mac OS X concentrating on the use of the Apple Core Video library routines for video processing. Completed: February 2009 1051.753 / Remote Sensing - Sensors and Image AnalysisView EvaluationsThis 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 1051.782 / Introduction to Digital Image ProcessingView EvaluationsThis 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 1051.799 / Graduate Independent Study
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. Completed: May 2003 Michael Foster (Graduate) 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. Completed: August 2004 Matthew Montanaro (Graduate) 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. Completed: May 2006 Sang-Yun Moon (Graduate) A self-directed study in object-oriented programming using the C++ programming language for image processing and medical imaging system modeling was undertaken. Completed: August 2006 May Arsenovic (Graduate) 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. Completed: November 2007 Jacqueline Spier (Graduate) An introduction to object-oriented programming in C++ with the purpose of understanding the numerical radiometric modeling in DIRSIG's photon mapping radiometry solver. Completed: November 2007 Sang-Yun Moon (Graduate) A competency in LabVIEW programming was obtained applied to the task of developing a control system for an electron spin resonance spectrometer for the Magnetic Resonnance Imaging laboratory. Visual programming of such tasks as ASCII control codes via RS232 and DAC/ADC board control were mastered during the course of this study. Completed: November 2008 Primary Advisor: Joseph Hornak
1051.840 / Masters Thesis ProjectGuidance 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 an advisor for the following students:
1051.890 / Research and ThesisGuidance 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 an advisor for the following students:Master of Science (7)
Doctor of Philosophy (3)
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) |