Table of Contents

10.   Matlab Lecture 10

10.1   Probability Distributions

10.1.1   Common PDFs
10.1.2   Randomly generated PDFs
10.1.3   Fitting normal distributions

10.2   Signal Processing - Digital Image processing

10.2.1   Filters
10.2.2   Smoothing / Blurring
10.2.3   Edge Detection
10.2.4   Sharpening
10.2.5   Filter and Sharpening in more detail
10.2.6   Line detection

10.3   Audio processing

10.3.1   Spectrogram
10.3.2   Filtering

10.3.2.1   Low-pass filter
10.3.2.2   High-pass filter
10.3.2.3   Stop-band filter

10.4   Discrete Cosine Transforms in Image Compression

10.4.1   1-dimensional compression
10.4.2   2-dimensional compression
10.4.3   Discussion
10.4.4   3-rd dimension compression

10.5   Discrete Cosine Transform in Audio Compression

10. Matlab Lecture 10

This lecture focuses on some selected statistical and signal (image and audio) processing techniques.

The following files are used throughout the lecture:

easyspec.m   Plot of power spectrum

specgram.m   Spectrogram plot

hanning.m   Hanning Window (used by easyspec.m)

em_1dim.m   Expectation Maximization - Approximation of Gaussian Mixture Models (GMM)

pomegranateSeeds.jpg   Picture of pomegranate seeds

building.jpg   Picture of building

funky.wav   Short funky sound file