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ECE 637: Digital Image Processing I

ECE 637: Digital Image Processing I (Spring 2011, Purdue University). Instructor: Professor Charles A. Bouman. Introduction to digital image processing techniques for enhancement, compression, restoration, reconstruction, and analysis. Lecture and laboratory experiments covering a wide range of topics including 2-D signals and systems, image analysis, image segmentation; achromatic vision, color image processing, color image systems, image sharpening, interpolation, decimation, linear and nonlinear filtering, printing and display of images; image compression, image restoration, and tomography. (from engineering.purdue.edu)

Lecture 28 - Chromaticity Diagrams and White Point

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Lecture 01 - Introduction

Lecture 02 - Continuous Time Fourier Transform and Continuous Space Fourier Transform

Lecture 03 - CSFT and Rep and Comb Relations

Lecture 04 - Optical Image Systems

Lecture 05 - Helical Scan Multislice CT (Computed Tomography) and PET (Positron Emission Tomography)

Lecture 06 - Tomographic Reconstruction: Fourier Slice Theorem and Filtered Back Projection

Lecture 07 - FBP (Filtered Back Projection) and Magnetic Resonance Imaging (MRI)

Lecture 08 - MRI Reconstruction

Lecture 09 - MRI and C-Programming

Lecture 10 - C-Programming

Lecture 11 - DTFT, DSFT, Sampling, and Reconstruction

Lecture 12 - 2-D Reconstruction and Focal Plane Arrays

Lecture 13 - Sampling and Reconstruction for Focal Plane Arrays

Lecture 14 - FIR and IIR Filters

Lecture 15 - IIR Filters and Random Variables

Lecture 16 - Random Variables and Random Processes

Lecture 17

Lecture 18 - Power Spectral Density and AR Processes

Lecture 19 - Eigen Signal Analysis

Lecture 20 - Eigen Signal Analysis and Edge Detection

Lecture 21 - Edge Detection and Connected Component Analysis

Lecture 22 - Segmentation, Clustering, and Color Vision Illusions

Lecture 23 - Achromatic Vision

Lecture 24 - Contrast, CSF (Contrast Sensitivity Function), and Achromatic Image Quality Metrics

Lecture 25 - Color Matching Functions

Lecture 26 - Color Matching Functions and Subtractive Color Systems

Lecture 27 - Subtractive Color Systems, Chromaticity Diagrams

Lecture 28 - Chromaticity Diagrams and White Point

Lecture 29 - White Point, Color Transforms, and sRGB

Lecture 30 - More Color Transforms

Lecture 31 - More Quality Metrics and Rate Conversion

Lecture 32 - Rate Conversion

Lecture 33 - Rate Conversion and Image Restoration

Lecture 34 - Image Restoration and Nonlinear Filtering

Lecture 35

Lecture 36 - Nonlinear Filtering and M-Estimators

Lecture 37 - Halftoning and Ordered Dither

Lecture 38 - Error Diffusion

Lecture 39 - Error Diffusion and RAPS

Lecture 40 - Entropy and Source Coding

Lecture 41 - Entropy and Source Coding

Lecture 42 - Lossy Source Coding and Rate-Distortion Theory

Lecture 43 - Rate-Distortion Theory

Lecture 44 - JPEG Image Coding