## 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 |