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DIP Lecture 1: Digital Image Modalities and Processing

DIP Lecture 2: The human visual system, perception, and color

DIP Lecture 3: Image acquisition and sensing

DIP Lecture 4: Histograms and point operations

DIP Lecture 5: Geometric operations

DIP Lecture 6: Spatial filters

DIP Lecture 7: The 2D Discrete Fourier Transform

DIP Lecture 8: Frequency domain filtering; sampling and aliasing

DIP Lecture 9: Unitary image transforms

DIP Lecture 10: Edge detection

DIP Lecture 11: Edge linking and line detection

DIP Lecture 12: Thresholding

DIP Lecture 12a: Image Segmentation

DIP Lecture 12b: Snakes, active contours, and level sets

DIP Lecture 13: Morphological image processing

DIP Lecture 13a: Region description and filtering

DIP Lecture 14: Object and feature detection

DIP Lecture 15: Lossless image coding

DIP Lecture 16: Lossy image compression

DIP Lecture 17: Image restoration and the Wiener filter

DIP Lecture 18: Reconstruction from parallel projections and the Radon transform

DIP Lecture 19: Fan-beam reconstruction

DIP Lecture 20: Dithering and halftoning

DIP Lecture 21: Digital watermarking

DIP Lecture 22: Image blending

DIP Lecture 23: Photomontage and inpainting

DIP Lecture 24: Image retargeting

DIP Lecture 24a: Digital Image Forensics

DIP Lecture 25: Active shape models

Description:

This course is an introduction to digital image processing. The course introduces the idea of what digital image processing is and where digital images come from, how images and colors are preceived by the human eye, coding for lossless and lossy image compression, and restoration of images among other topics.

Intro to Digital Image Processing Lectures, Spring 2015

Rensselaer Polytechnic Institute

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#Computer Science #Digital Image Processing #Engineering #Electrical Engineering #Signal Processing #Fourier Transform #Artificial Intelligence #Computer Vision #Edge Detection #Data Science #Data Visualization #Histograms

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