I’ve been excited about the possibilities of advanced algorithms in processing pictures, both to increase resolution and reduce noise. When used in combination on an initially noisy image, however, the results can be… unpredictable. Though this image looks fairly reasonable on the web page, clicking through to the full-resolution version on Flickr shows some exciting rogue AI strangeness—like odd places of varying noise reduction.
My favorite William Gibson quote is, “The future is already here—it’s just not very evenly distributed.” How we gauge futurity—or how we identify the traits we associate with future-ness—means that some places will have more “future” to them than others. A mountaintop in the Adirondacks might be pretty similar to its condition 100 years ago, while downtown Berkeley would be unrecognizable.
This image is a picture of the past, from the “future”: I wanted to print a tall, vertical image of Berkeley and the Bay but had (it turns out) never quite taken the one I wanted. I had taken the two pictures that went into making this image as part of a larger panorama in 2013 that never quite came out. Here in the present, I pulled in every technique in my arsenal—Adobe’s super resolution, Topaz AI noise reduction, frequency separation—to assemble two images from a circa-2010 16 MP Nikon D7000 into the 76 MP monster you see below. This one is definitely worth clicking through to full resolution.
While my normal images capturing the “civilization gradient” tend to be more focused on space (traversing from nature to dense urban areas), I sort of like the way this image reminds me of a traversal through time, from the Stone Age to the Information Age. As William Gibson says, “The future has already arrived—it’s just not very evenly distributed.”
Or perhaps it really just reminds me of the vantage point from Caspar David Friedrich’s “Wanderer above the Sea of Fog“.
This image is another in a series of my re-processings of less-than-new RAW files with Photoshop’s “Super Resolution” machine learning algorithm. As in those other cases, the added impression of detail is particularly astonishing when viewed at full size after clicking through to the original image on Flickr.
Extracting additional information from an image by “enhancing” it has long been a ridiculous trope of police procedurals; it’s with great amusement that I noticed that Photoshop’s new “Super Resolution” capability (which uses machine learning to quadruple the resolution of an image) is under an option called “Enhance”. The first subject for enhancement was this picture I took of Berkeley and San Francisco in 2011. It’s worth the click-through for the full resolution version.
(Adding to the super-resolution theme, this image also contains, in the lower-center, the Molecular Foundry and its associated center for electron microscopy.)
Views like this one, capturing the marine layer rolling across the San Francisco Bay towards the Port of Oakland, are the kind that first attracted me to photography. I took this picture nearly four years ago, during my sabbatical to the Bay Area, when I was still shooting with my Nikon D7000 (already antiquated tech in 2017); I can’t want to be able to safely revisit Berkeley’s Grizzly Peak to capture more cityscapes with my new Sony a7R IV.
My favorite view of the Bay Area (and the view that first let me define the idea of the civilization gradient as an element of my photography) is layered up with loads of detail. Down in Berkeley Lab is the building where I worked on sabbatical, and across the Bay Bridge is the completed Salesforce Tower hiding in the marine layer. The differences, particularly from the last time I showed a very similar shot from the spring, are in nature: the high-altitude clouds have been replaced with empty skies and that rolling marine layer, while the green hills have shifted to a dry, highly flammable tan.
Two of my past St. Lawrence University students are working on their Ph.D.s at Berkeley and I discovered yesterday that one was giving her Graduate Research Conference (Berkeley’s version of a thesis defense, but earlier) while the other was in the audience. I’m very proud of both of them.
Understandably, this had me thinking about my experiences at Berkeley. In this picture from Grizzly Peak, the perspective folds together Oakland, San Francisco, and Berkeley. In the foreground, look at those gnarled trees—they’re weird but they’ve grown tall. I’ll take that visual metaphor for the grad school experience. I took this picture on Christmas Day in 2016, so I guess that makes these Christmas trees, too.
I took this picture two years ago, during a wonderful springtime in Berkeley when a rainy winter had made the hills lush and green. The view is enormous, overwhelming: Oakland, San Francisco, Emeryville, and Berkeley all packed into one. I like the contrast of the tiny path on the green hilltop on the left side of the image providing a quiet contrast.
I finally finished processing the photographs of the transcontinental drive, transient spectroscopy, and Transamerica pyramid that made up my 2017 sabbatical from St. Lawrence University to Berkeley Lab for solar energy research. Check out my favorites, in handy chronological order, by clicking on the image of Alcatraz and the Golden Gate Bridge below: