Image Processing

This lecture was a continutation of past lectures in which we learned about the different types of resolution.  Here, we looked at some specific mathematical and statistical properties of image data.  In image processing, an image can be represented as matrix values.  Because of this, it is easy to pinpoint certain data values.  Various subsets of image processing were discussed, such as data interpolation, image restoration, and image segmentation.  The types of digital images include binary, grayscale, true color, and indexed color.  Also, basic statistical and manipulation methods were introduced that could help describe and change imaging properties.  Histogram equalization was one statistical method.  Histograms are a way of displaying the distribution of image data.  Also, various functions were described that could change the appearance of the image.

Listed below is a very interesting, informative, yet easy to understand series of lectures on digital image processing.  Images were manipulated using MATLAB for class assignments.  It made me want to take pictures and do assignments! :)

http://eeweb.poly.edu/~onur/lectures/lectures.html

Posted by Annie