Concept

Wavelet

Related lectures (30)

Explores image coding, compression techniques, and wavelet-based methods for efficient data representation.

Covers worked examples on hypothesis testing and non-parametric regression.

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

Explores challenges in sampling and reconstructing high-dimensional visual appearance using signal processing techniques.

Introduces signal acquisition, GMWM for sensor calibration, and the importance of accurate parameter matching.

Covers Parseval relations, Fourier series, energy calculation, and correlation in signal processing.

Explores model reduction techniques for satellite positioning systems and stochastic sensor calibration using the GMWM method.

Explores non-parametric regression techniques, including splines, bias-variance tradeoff, orthogonal functions, wavelets, and modulation estimators.

Explores B-spline properties, gradient operators, interpolation, and differentiation filters in image processing.

Explores image segmentation, thresholding techniques, texture segmentation, and connected-component labeling in image processing.