Signal & Image Processing

Watch

• But what is a convolution? ↗3Blue1Brown
• But what is the Fourier Transform? A visual introduction. ↗3Blue1Brown
• Lanczos Resampling Digital Signal Image Processing - Aditya Mittal - AcmeTutor - Sinc function ↗Aditya Mittal

Read

• Signals and Systems ↗An indispensable primer for understanding the fundamental principles that underpin all modern signal analysis, from audio compression to medical imaging.Alan V. Oppenheim, Alan S. Willsky, S. Hamid Nawab
• Digital Image Processing ↗The definitive textbook, offering a comprehensive and practical guide to the algorithms and techniques central to manipulating and interpreting visual data.Rafael C. Gonzalez, Richard E. Woods
• The Scientist and Engineer's Guide to Digital Signal Processing ↗An exceptionally clear and intuitive introduction, demystifying complex concepts for practitioners without requiring a deep mathematical background.Steven W. Smith
• An Algorithm for the Machine Calculation of Complex Fourier SeriesThe seminal paper that introduced the Fast Fourier Transform, revolutionising computational signal analysis and enabling countless modern technologies.James W. Cooley, John W. Tukey
• A Theory for Multiresolution Signal Decomposition: The Wavelet RepresentationA foundational work establishing the mathematical framework for wavelets, providing a powerful tool for multi-scale signal analysis and compression.Stéphane G. Mallat

Voices to follow

• Ingrid Daubechies ↗A pioneer in wavelet theory, her work underpins modern image compression and signal analysis, from medical imaging to digital photography.Mathematician, Professor at Duke University
• Emmanuel Candès ↗A leading architect of compressed sensing, a revolutionary technique for acquiring and reconstructing signals and images from far fewer measurements than traditional methods.Mathematician, Professor at Stanford University
• Alan V. Oppenheim ↗His foundational textbooks and research have shaped generations of engineers and scientists in the principles and applications of digital signal processing.Professor Emeritus of Electrical Engineering, Massachusetts Institute of Technology (MIT)
• Stéphane Mallat ↗Renowned for his contributions to wavelet theory and sparse representations, he has developed fundamental tools for analyzing and understanding complex signals and images.Professor of Applied Mathematics, Collège de France and École Normale Supérieure

Glossary

• AnalogAnalog refers to information that is continuous and changes smoothly, like real-world sounds or light. It's not broken into separate numbers. For example, the sound waves from a guitar string vibrating are an analog signal before they are recorded digitally.
• CompressionCompression is the process of making a digital file smaller without losing too much important information. This makes it easier to store and share. For example, when you save a photo as a JPEG file, it's usually compressed so it takes up less space on your phone or computer.
• DigitalDigital means information is stored and processed using numbers, usually 0s and 1s. This makes it easy for computers to handle. For example, a song downloaded to your phone is a digital signal, made up of many tiny numerical pieces.
• FilterA filter is a tool or method used to change specific parts of a signal or image, often to remove unwanted parts or enhance others. For example, an "unsharp mask" filter in photo editing makes the edges in an image look crisper and more defined.
• ImageAn image is a visual representation of something, like a photo or a drawing. It captures light and color information from a scene. For example, a picture you take with your phone camera is an image that captures a moment in time.
• NoiseNoise is unwanted random information that interferes with a signal or image, making it harder to see or hear the actual content. For example, the static sound you hear on a bad radio station is audio noise, making it hard to understand the music or speech.
• PixelA pixel is the smallest individual dot or square that makes up a digital image. Each pixel has its own color and brightness. For example, if you zoom in very close on a digital photo, you'll start to see the tiny colored squares, which are pixels.
• ProcessingProcessing means changing or improving a signal or image for a specific purpose. This could be to make it clearer, smaller, or to find certain details. For example, when you apply a filter to a photo on social media, you are processing the image to change its look.
• ResolutionResolution describes how much detail an image or display can show. Higher resolution means more pixels and a clearer, sharper picture. For example, a TV with "Full HD" resolution has many more pixels than an older TV, making the picture look much sharper.
• SignalA signal is any information that changes over time or space, like sound waves or light. It carries data we can measure and study. For example, when you speak into a microphone, your voice creates a sound signal that changes as you talk.

Threads 8

Where this connects to other fields, and why it's worth knowing.

• Perception & Attention Psychology

  Your eyes actually send the brain a blurry, upside-down picture with a literal blind spot hole in it. The crisp, steady world you 'see' is your brain guessing and filling in the gaps, prediction over raw data. So seeing isn't a camera recording reality; it's more like a lightning-fast sketch artist inventing the missing bits.

• Film & the Moving Image Arts & Design

  In old movies the wagon wheels sometimes look like they're spinning backward. That's because the camera only snaps 24 pictures a second, too slow to catch the fast spin, so your brain reads it wrong. The exact same speed limit, called the Nyquist limit, decides how fast every phone and computer has to sample sound and video to not mess it up.

• Satellite Imagery and Remote Sensing Geography

  A satellite 'photo' of Earth isn't really a photo. It's a picture rebuilt from raw sensor readings using the same math that turns an MRI scan into an image of your knee. In both cases you never see the thing directly; you work backward from clues to reconstruct what must be there, which mathematicians call solving an inverse problem.

• Digital Health & Telemedicine Health

  When your smartwatch warns of a weird heartbeat, it's doing signal processing right on your wrist. It uses the same filtering math that pulls a clear song out of a staticky radio. That math takes your jittery, noisy pulse and cleans it up enough to spot a real problem, no doctor's office required.

• Poetry Literature

  Before writing, poems survived only by being memorized and retold for centuries. Rhyme and rhythm are the trick: if a storyteller misremembers a line, the broken rhyme instantly sounds wrong, so it gets fixed. That's exactly how error-correcting codes protect data, catching a mistake because it no longer fits the pattern.

• Music & Sound Arts & Design

  An MP3 shrinks a song by deleting sounds your ears literally can't hear, like a soft note hidden right after a loud crash. This 'masking' is a blind spot in human hearing, and the whole compression trick is built directly on top of it. You're not missing anything, because your brain was going to ignore it anyway.

• Photography Arts & Design

  Before you even see a digital photo, your phone has rebuilt it: guessing colors, wiping out noise, and squishing the file smaller. So a photo that supposedly 'proves what happened' is already a computer's best guess, dressed up to look like raw reality.

• Electrical & Electronics Engineering Technology

  Circuits measure and carry signals; processing methods help distinguish wanted information from noise.

  Sources: U.S. Bureau of Labor Statistics — Electrical and Electronics Engineers ↗ · ABET engineering program criteria 2025–2026 ↗