Image Processing Basics

Related lectures (31)

Page 3 of 4

Covers advanced design techniques for CMOS cameras, focusing on pixel architecture and noise management in active pixel sensors.

Covers search algorithms, focusing on abductive reasoning and heuristic search strategies.

Covers practical image processing using Fiji software, emphasizing data quality importance.

Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.

Covers denoising and reconstructing images using total variation minimization and discusses the visual effects of different regularization strengths.

Introduces image processing basics in Python, covering manipulation, grayscale conversion, edge detection, and convolution with kernels.

Covers the notation and key concepts related to digital images and 2D signal representations.

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

Covers colors, scientific images, and image dimensions beyond 2D planes.

Covers the definition of digital images, image formation, classification by bit depth, and image analysis.