Lecture

Image Processing I

In course

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Description

This lecture covers the basics of image processing, focusing on digital filtering, linearity, shift-invariance, convolution, and filter characterizations. It explains how to implement filters using masks, the concept of separability, and direct products. Examples of local average and vertical-edge enhancer filters are provided, along with their transfer functions and frequency responses. The lecture also discusses recursive filtering and z-transform in the context of image processing.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_rr7ay2yq

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Ontological neighbourhood

Information engineering

Signal processing: Filtering theory

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