Image Processing: Neighborhood Averaging & Gaussian Smoothing

Related lectures (29)

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Covers techniques for reconstructing color images using optical detection and artificial intelligence to enhance image quality and reduce noise.

Explores discrete histogram processing and spatial operators for image manipulation and noise reduction.

Covers edge detection, texture analysis, Canny's algorithm, filterbanks, and segmentation techniques.

Explores topology concepts and edge detection in computer vision, highlighting the significance of contours and gradients in image analysis.

Explores correlation measures, matched filtering, and feature extraction in image processing.

Discusses edge detection techniques and the evolution of deep learning in neural networks.

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Explores image filtering techniques, including linear and nonlinear filters, for artifact removal and feature enhancement.

Covers scientific image processing fundamentals, software practices, and ethical considerations in image processing.

Explores directional image analysis and the implementation of steerable filters for edge and ridge detection.