During my current course 'Data Anaylsis and Interpretation', in which our course instructors are Image processing specialists we have worked on several interesting assignments on this topic and implemented them in MATLAB. One of them was the PDF Estimator where we compared various non parametric estimation techniques like histogramming and Kernel Density Estimation and implemented cross-validation procedure, an application of Machine Learning. In another problem, we were given two Magentic Resonance Images (MRIs) of a portion of human brain, acquired with different settings of the MRI machine. After casting the images as a double array, we were asked to shift the second image by various amounts and for each compute the correlation coefficient (CC) and quadratic mutual information (QMI) for the first image and shifted versions of second image. The major point was to realise after several plots was that QMI is a much stronger indicator than the CC and anaylze why so.
To run the code, put all in the same directory and run q6_1.m and the plots will be generated.