Learn how machines see, one kernel at a time.
Tutorials that go from image arrays and filters to feature matching, classic machine learning and modern deep networks. Each one has the intuition, the math, code you can run, and a demo you can play with.
The curriculum
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All posts →Images as Arrays
What a digital image really is, and how NumPy and OpenCV store it.
Oct 4, 2026Image Processing · BeginnerChapter 1 · Introduction
What digital image processing is, where it came from, which parts of the electromagnetic spectrum it works with, and the roadmap of fundamental steps this series follows.
Oct 4, 2026Image Processing · BeginnerChapter 2 · Digital Image Fundamentals
How eyes and cameras turn light into numbers, how sampling and quantization shape a digital image, and the basic math every later chapter builds on.
Oct 4, 2026Image Processing · BeginnerChapter 3 · Intensity Transformations and Spatial Filtering
Remap pixel values with curves and histograms, then smooth and sharpen images with small kernels: the everyday toolbox of spatial-domain enhancement.
Oct 4, 2026Image Processing · BeginnerConvolution & Image Filtering
Blur, sharpen and find edges by sliding a 3×3 kernel across an image.
Oct 4, 2026Image Processing · IntermediateChapter 4 · Filtering in the Frequency Domain
How the Fourier transform turns an image into a recipe of waves, and how editing that recipe smooths, sharpens and removes periodic noise.
Oct 4, 2026