Image scaling

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Related lectures (10)

Resizing, Interpolation and Image Math Introduction

Covers resizing, interpolation, and basic image math operations with practical examples.

Image Scaling and Math

Covers image scaling, interpolation, artifacts, pixel sizes, and bit depth.

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Practical Sampling and Interpolation

Covers practical sampling, interpolation challenges, spectral representation, and Fourier Transform properties.

Oversampled D-A: Interpolation and Distortion

Explores oversampled D-A conversion, interpolation methods, and in-band distortion compensation.

Spectral Representation: Downsampling

Covers the spectral representation of downsampling and rational sampling rate change.

The spectrum of interpolated signals

Explores sinc interpolation and the spectral representation of interpolated signals based on the chosen interpolation period.

Polynomial Networks: Spectral Bias Analysis

Delves into the spectral bias of polynomial neural networks, analyzing the impact on learning different frequencies and discussing experimental results.

Sinc Interpolation

Covers Lagrange interpolation, local schemes, and sinc interpolation convergence.

Medical Image Reconstruction: From Model-Based to Data-Driven

Explores the evolution of medical image reconstruction techniques, from classical methods to data-driven approaches using deep neural networks.

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