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.