Digital Image Filtering Lecture

Abstract

This lecture overviews Image Filtering, which is very important to ensure high image quality and image denoising.  It covers the following topics in detail: Image noise. 2D FIR filters, including Moving average filters. Spatial filters. Median filter algorithms. Digital filters based on order statistics, e.g., max/min filters and L-filters, Adaptive order statistic filters. Anisotropic Diffusion. Image interpolation.

Crack filling in a Byzantine painting using anisotropic diffusion.

Ultrasonic image filtering.

Digital-Image-Filtering-v3.4-Summary

Tutorial Exercises

1. Average Sampling For Noise Reduction Tutorial Exercise
2. Root-signal Median Filtering Tutorial Exercise

Programming Exercises

1. Digital Image Filtering Using OpenCV
2. Image Noise
   1. Gaussian Noise
   2. Salt and Pepper Noise
   3. White Multiplicative Noise
3. Median Filters
   1. Multistage Median Filter
   2. Running Median Filter
   3. Standard Median Filter
   4. Weighted Median Filter
4. Moving Average Filter
5. Running Max,min Filter
6. Conservative Smoothing
7. Gaussian Smoothing
8. Image Interpolation
   1. Image Decimation
   2. Image Zooming
   3. Zero-Order Hold Interpolation