Filtering, enhancement and edge detection of 2D signals.
Digital images are arrays of pixels. Operations: histogram equalisation, filtering (Gaussian blur, sharpening), edge detection (Sobel, Canny), morphology, thresholding and segmentation, geometric transforms, colour spaces, compression (JPEG, PNG). 2D convolution and FFT are central.
A Sobel kernel highlights edges by computing intensity gradients.
Image processing applies signal ideas to two-dimensional data, which underpins cameras, medical scanners and quality inspection.
Filtering, enhancement and edge detection of 2D signals.
Image processing applies signal ideas to two-dimensional data, which underpins cameras, medical scanners and quality inspection.
A place where brightness changes rapidly, which shows up as a large gradient and is detected by filters such as Sobel or Canny.
Its values define the operation, so a smoothing kernel blurs and an edge kernel highlights changes.
Typical applications include enhancing the contrast of an X-ray image, detecting edges of parts on a production line and removing speckle noise from an ultrasound image.
Study "Wavelets" first (topic 38 of 101 in Signals, Control & Comms). It covers the groundwork this topic builds on.
Kernels. Aliasing in images. OpenCV.
A Sobel kernel highlights edges by computing intensity gradients.
The next topic is "Audio and speech processing", which builds directly on this one.
It is classed as Intermediate in Signals, Control & Comms (topic 39 of 101). It is an intermediate topic. Work through the beginner topics in Signals, Control & Comms first.
Want to practise? Open the interactive course for quick checks, quizzes, simulations and progress tracking.