"LACMA’s website has begun releasing publication-quality digital images of out-of-copyright works in its permanent collection. It appears to be the first major museum to do this, and that’s big news. It may herald the end of 'zombie copyrights.'"

"Noam Galai took a few photos of himself in 2006 and uploaded them to his Flickr. A few people liked those photos, but he didn't think of it. Over time, he began to see his photos popping up all over magazines, the internet and as street art. Then it began appearing on commodities (clothes, books, etc.). Now, it's being used as a symbol of protest in Iran. The crazy part is that nobody asked his permission.

Fstoppers are responsible for this great video narrative, titled The Stolen Scream, which details Galai's story, and the process of watching himself become an anonymous global icon with no control over how his image is used (in one case, the photo was attributed to someone else entirely). He even mentions that when he tried to register the photo with sites like Getty Images, they told him the image would never sell.

All in all though, it's a great story about the dissemination of digital media over the Internet and the inevitable conflict between those who create it and those who use it"

"The Laboratory for Intelligent Imaging and Neural Computing (LIINC) was founded in September 2000 by Paul Sajda. The mission of LIINC is to study fundamental processing strategies and representations used by biological vision systems and apply these to develop artificial vision systems capable of sophisticated and adaptive image and scene analysis. Our laboratory pursues both basic and applied neuroscience research projects, with emphasis in the following:

Network models for visual processing
Neuroimaging
Statistical representation of natural signals
Machine Learning"

More on Neuromatters
"The human brain reacts to images of interest at a pace that is far faster than a person can consciously register. Researchers at Columbia University have developed a technology, “Cortically Coupled Computer Vision (C3Vision)”, that takes advantage of this near-subconscious ability and pairs it with the processing power and efficiency of computers for rapid identification of images that the brain finds relevant.

C3Vision relies on a suite of patented machine learning algorithms which are trained to recognize what is of interest to a human viewer in a given context. Wearing an electroencephalography (EEG) cap with electrodes that capture electrical activity of the brain, a person is shown a sequence of images at a rapid pace. Each time an image of interest is displayed, the brain emits a distinctive electrical signal which is captured and decoded by the technology. Based on the strength of these neural responses, images are ranked. Over time, the technology learns what types of images are of interest to the viewer, and can eventually identify such images on its own.

“Computer vision systems are good at crunching through lots of data, but rather poor at characterizing images and scenes based on abstract and subjective concepts such as ‘that’s interesting’ or ‘I like that’ ,” said Paul Sajda, PhD, Director of the Laboratory for Intelligent Imaging and Neural Computing and a Professor of Biomedical Engineering and of Radiology at Columbia University’s School of Engineering and Applied Science and Columbia University Medical Center, respectively. “In contrast, the human visual system is exceedingly good at abstract and subjective scene analysis and image understanding, though would obviously be overwhelmed by having to analyze information from millions of images.

With a combined $4.6 million of support from DARPA Neuromatters and Columbia are collaborating on the development of an integrated image triage system based on the C3Vision technology. The system will be used and evaluated in operational environments by government image analysts to examine vast areas of satellite imagery for specific physical characteristics. The system may also extend to video surveillance and security, where the aim is to identify suspicious activity."

Image Retouching: A Critical Approach for Media Arts Educators
I developed the following course unit on image tampering, retouching and manipulation for my Introduction to the Electronic Media Studio (EMS1) class at Carnegie Mellon. The semester course is intended for first-year students with little or no computer experience, and serves the purpose of introducing students to basic media-editing tools. The emphasis in the course is not on technical mastery but on understanding digital media technologies as tools for creative cultural practice.

The loosely-organized materials I’ve cited below provide starting points for discussions about image manipulation from several perspectives, including: photojournalistic standards of truthtelling; the construction of idealized beauty in vernacular advertising; and the early history of 19th-century photocollages as an extension of narrative romantic painting.