EE 5372 Image Processing

Signal processing theory and techniques is the base for the image processing, and video processing. Traditional image processing always expect a result for the application of the traditional algorithms such as: image enhancement, denoise, contrast, etc.
However, as introduced by Dr. Cabrera, in this course we will see a more advanced an deep understanding of the mathematical concepts that involve image analysis, transformation, compression, without necessarily see a visual output.
I took a DIP (digital image processing) course on my masters degree, and we based the course on the Gonzalez book, therefore, I got used to a notation: I(x,y), to refer to an image with x rows and y columns. Apparently, in this course the author introduces a different notation: x(n1, n2), which is very similar to the signal processing notation: x(n). This is obviously in the discrete domain. See the picture of the notation, and an example of graphical representation. This is very different from MATLAB representation, and from Gonzalez book.

EE 5390 /16644 Biomedical Imaging and Imaging Informatics

Nobel prizes, and very promising research topics for science/engineering students, is what one can achieve if directed, trained, and experimented over the Biomedical Imaging and Imaging Informatics field. Take a look at this video that shows a clear application of Biomedical Imaging: The Cancer.



Here are some other videos shown in class on line:
http://uwf.edu/sahls/courses/hsa5197/CourseOverview/Mod1/Introduction%20To%20Medical%20Informatics/player.html

and:





Today we were introduced to this field. And also the professor gave us the syllabus.