Image Processing: Basics and Techniques

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Introduces image processing techniques in Python, focusing on manipulation and convolution operations using NumPy and Pillow.

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

Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.

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

Covers the basics of image processing using Fiji software, focusing on managing files and applying filters.

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

Explores Greyscale, color, and special image types, bit depths, RGB creation, and file formats.

Covers the basics of image acquisition, including optical devices, resolution factors, lens distortions, and sensor technologies.

Covers the theory and algorithms behind image segmentation, focusing on region identification and evaluation.

Covers the creation of a poster using Illustrator, focusing on color, layers, opacity, and file management.