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Lecture
Image Processing Basics
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Related lectures (31)
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Image Processing in Python: Manipulation and Convolution Techniques
Introduces image processing techniques in Python, focusing on manipulation and convolution operations using NumPy and Pillow.
Image Processing: Neighborhood Averaging & Gaussian Smoothing
Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.
Image Filtering: Classic Filters
Explores classic image filters like Moving Average, Gaussian Blur, Sobel filter, and Laplacian operator.
Image Processing: Enhancement and Analysis
Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.
Computer Vision Basics: Image Processing and Feature Detection
Covers the basics of computer vision, focusing on image processing techniques and feature detection.
Image Processing Techniques
Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.
Image Processing: Basics and Techniques
Introduces image processing basics, covering vector vs matrix images, RGB color system, grayscale, and image manipulation libraries.
Mercer Theorem and Kernels
Explores the Mercer Theorem, Kernels, and their role in machine learning applications.
Image Processing: Smoothing and Filtering
Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.
Image Processing I: Edge Detection and Texture Analysis
Covers edge detection, texture analysis, Canny's algorithm, filterbanks, and segmentation techniques.
