image processing

A six-minute clip of Adobe's MAX 2011 sneak peek showing a Photoshop prototype that removes motion blur from photos. The audience reacts with astonishment as blurry images become legible.

A short explainer from Nat and Friends on where Google Earth's 3D imagery comes from, how it is stitched together, and how often it is updated. It describes aircraft carrying camera rigs and photogrammetry that turns the photos into 3D models.

A short conference talk from !!Con 2017 in which Kevin Chen explains the HDR imaging algorithm from a foundational paper, framing it as a system of linear equations, and implements it in a Microsoft Excel spreadsheet. No prior image processing knowledge is needed.

The first lecture of Stanford's Natural Language Processing with Deep Learning course, taught by Chris Manning and Richard Socher. It introduces NLP and word vectors, including SVD, skip-gram, CBOW, negative sampling and word2vec.

A short video accompanying the CVPR 2018 paper Learning to See in the Dark. It shows a neural network producing sharp images from very low-light raw sensor data, compared against denoising approaches.

A one-minute scene from the film Enemy of the State showing absurdly implausible image enhancement, with freezing, rotating, zooming and focusing on a video.

A SIGGRAPH Asia 2013 research demo of 3-Sweep, a tool for extracting editable 3D objects from a single photo using a few user strokes. It predates modern AI image tools.

A guest video by Welch Labs on 3Blue1Brown explaining how text-to-image and video models work. It covers CLIP, shared embedding spaces, diffusion models (DDPM, DDIM), conditioning, guidance and negative prompts.

A one-minute clip from a CSI episode featuring the trope of zooming and enhancing low-resolution images. The uploader says it was the last CSI episode they watched.

A two-minute supercut of film and TV characters ordering a computer to 'enhance' a blurry image into a perfectly sharp one. It is a remaster of an earlier 2009 version.

A two-minute compilation of TV and film scenes where investigators say 'enhance' and a blurry image becomes sharp. It mocks the trope.

Andrew Adams, a Halide developer, presents the Halide language for image processing and tensor computation. The talk explains the separation of algorithm from schedule with illustrated examples of parallelism, locality and redundancy tradeoffs.

The Thought Emporium shows how to receive clear images directly from GOES-15, 16 and 17 and Himawari 8 geostationary weather satellites with software-defined radio. It covers the extra effort needed to receive GOES data.

A short Harris Corporation (L3Harris) promotional video showing wide-area airborne motion imagery, a sensor system for persistent real-time aerial surveillance of large areas.

Lesson 1 of fast.ai's Practical Deep Learning for Coders, taught by Jeremy Howard. It takes coders from running code in a Jupyter notebook straight into training a real image model.

The first lecture of Stanford's CS231n course on convolutional neural networks for visual recognition. It surveys the history and key challenges of computer vision, from the Cambrian explosion and Hubel and Wiesel to ImageNet.

A 2006 Google TechTalk in which Luis von Ahn introduces human computation, using people's effort to solve problems like image recognition that computers cannot yet handle. It covers games with a purpose and related ideas such as CAPTCHAs.

An HBO clip from Silicon Valley season 4 in which the 'Not Hotdog' app is demoed. The app classifies food photos as hot dog or not hot dog.

Adobe's sneak-peek demo of Content-Aware Fill ahead of Photoshop CS5, showing objects being removed and areas repaired seamlessly with the delete key.

The Blade Runner scene in which Deckard uses a voice-controlled machine to enhance a photograph, zooming into hidden details.

GeoGuessr pro Rainbolt plays head-to-head against an AI built by Stanford students that guesses locations from street-view images. The video shows the AI repeatedly beating him.

MinutePhysics explains that computers store brightness nonlinearly, so blurring and blending colors in raw RGB gives wrong, dark results. It shows why mixed colors, such as in gradients, look off.

Alex O'Connor shows that ChatGPT cannot draw a wine glass filled to the brim, and ties the failure to David Hume's missing shade of blue. It asks what the failure says about how image models learn.

A short side-by-side demo of a large image loading over a slow connection in JPEG, progressive mozjpeg, JPEG XL and AVIF. It shows how each codec renders partial data.

Samuel Falvo II live-codes a text preprocessor and blog engine in Forth over about an hour. It shows Forth's dictionary being snapshotted and restored in place of mutation, and how a small Forth system gets real work done.

Mike Pound explains the discrete cosine transform and how it underpins JPEG compression. It is part two of Computerphile's JPEG series.

MIT researchers show that sound can be recovered from silent video by analyzing tiny vibrations in objects such as a potato chip bag. It works even with consumer cameras by using rolling shutter.

A short demo video for NVIDIA's StyleGAN paper, which proposes a style-based generator for GANs. It shows face synthesis with style mixing and scale-specific control over attributes like pose and freckles.

The first lecture in an 18-part series on digital photography from Marc Levoy's Stanford CS 178 course, recorded at Google in 2016. The series covers how digital cameras work and computational photography, with slides and assignments available on the course site.

Benn Jordan's video about storing a PNG image in a living bird, a starling that learns to reproduce encoded sounds. It mixes ornithology, audio engineering, and data encoding.

Peter Norvig, then Director of Research at Google, talks at Startup School 2008 about leveraging large amounts of data and about technical challenges in Google projects such as image search. A central idea is that data can beat hand-written programming.

Veritasium visits the US Navy's Crane facility to test top night vision goggles. It explains how image intensifier tubes and thermal or digital systems work and compares the generations of the technology.

Jessie Frazelle's DockerCon SF 2015 talk on running Docker containers for desktop applications, with fun container hacks and images. It shows how far containers can be pushed beyond servers.

A short Techquickie explainer on why laptop webcams are much worse than phone cameras. It covers sensor size, image processing, and the interface differences between laptops and phones, with input from a Logitech engineer.

A spectrogram analysis of Aphex Twin's track commonly called [Equation] from Windowlicker, rendered from a lossless version. At about 5:30 the spectrogram reveals an image of Richard D. James's face.

A King of the Hill clip in which Hank-style character rants about saving images as PNG instead of JPEG after exporting from Windows Paint.

The SIGGRAPH 2005 demo of dual photography from Stanford, which swaps the roles of projector and camera to render a scene from the light's point of view. It includes the reveal of a hidden playing card.

Tom Scott visits the USPS Remote Encoding Center in Salt Lake City, where keyers decipher mail images machines cannot read. It shows the lengths taken to decode bad handwriting.

A University of Tokyo lab demonstrates a book scanner that flips pages automatically and scans over 250 pages per minute. It uses real-time 3D recognition of the flipped pages and then restores each one to a flat image.

Berkeley neuroscientist Jack Gallant shows how fMRI brain mapping can be used to decode what a person sees, with visualizations of brain activity and its implications.