Image Filtering: Classic Filters

Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.

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

Covers edge and contour detection in images, including gradient-based methods, Laplacian operator, and more complex methods.

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

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.