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Time–frequency analysis

Applied sciences
Information engineering
Signal processing
Time–frequency analysis

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Covers advanced topics in watermarking, including resisting scaling and rotations, self-referenced watermarking, and types of attacks.

Image Processing I

Introduces the basics of image processing, covering point and spatial operators, histogram processing, and transform-domain operations.

Image Processing II: Optimal Transforms and Applications

Explores optimal transforms, image applications, linear algebra, and 2nd-order statistics in image processing.

JPEG 2000: Image Compression

Explores image compression principles, focusing on JPEG 2000, covering transform-based coding, quantization, entropy coding, region of interest, error resilience, and software implementations.

Probabilistic Models for Linear Regression

Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.

Linear Regression: Statistical Inference and Regularization

Covers the probabilistic model for linear regression and the importance of regularization techniques.

Spectral analysis and stationarity tests

Covers spectral analysis, stationarity tests, challenges of nonstationary time series, and tools for analysis with missing data.

Image Processing Labs with Jupyter Notebooks

Covers the development of Jupyter Notebooks for image processing labs with automated suggestions for students.

Data Compression: Sparse Signals and Data Recording

Explores data compression through signal sparsity, questioning the need for recording vast amounts of data.

Image Processing II

Explores image interpolation, splines, wavelets, and geometric transformations in image processing.