Lectures related to Image Filtering: Basics and Techniques

Image Processing Techniques

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.

Digital Filtering Fundamentals

Introduces fundamental notions in digital filtering, covering 2D filtering approaches, linear filters, stability, FIR and IIR filters, frequency domain filtering, and Gaussian filters.

Image Processing: Smoothing and Filtering

Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.

Image Processing I: Filters and Transformations

Explores moving average and exponential filters, Gaussian filtering, and linear scale-space concepts in image processing.

Linear Phase Filters: Step Response and Characteristics

Explores linear phase filters, rise time, Gaussian filters, and rational transfer functions.

Image Processing: Enhancement and Analysis

Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.

Time Series: Spectral Analysis and Linear Filtering

Explores spectral analysis, aliasing, and linear filtering in time series data.

Image Filtering: Summary

Covers the fundamental principles of image filtering in biomedical analysis.

Active Filters: Second-order and High-order Realizations

Covers the design and implementation of active filters, focusing on second-order and high-order realizations.

Feedback and Stability: Active Filters

Explores feedback, stability, and active filters, covering various amplifier structures, filter fundamentals, and stability analysis.

The convolution theorem

Explores the convolution theorem, DTFT reconstruction, frequency response effects, and signal building.

Fourier Transform and Convolution Product in Signal Processing

Explores the Fourier transform, convolution product, and their applications in signal processing.

Digital Filters: Frequency Response Approximation

Explores digital filter synthesis, emphasizing frequency response approximation and pole-zero placement.

Digital Filters: RII Filters - Part 2

Covers digital RII filters, elliptical and Chebyshev filters, frequency transformations, and filter realization.

Image Processing I: Filter Design and Boundary Conditions

Explores filter design, boundary conditions, Fourier-domain filtering, and useful smoothing filters for image processing.

Filters Fundamentals: Chebyshev Polynomials and Filter Design

Covers Chebyshev polynomials, all-pole filter design, RLC filters, and active-RC and OTA-C filter implementations.

Convolution of Distributions and Differential Equations

Explores the convolution of tempered distributions and solving differential equations using fundamental solutions.

Linear Estimation and Prediction

Explores linear estimation, Wiener filters, and optimal prediction in signal processing.

Signal Processing: Image Restoration and Linear Prediction

Explores image restoration and signal prediction using linear filters in signal processing.

Parametric Signal Models: Matlab Practice

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.