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 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 |