Monthly Archives: November 2006

A shiny black box of secrecy

I’ve been threatening to take Lisa to the National Cryptologic Museum for many years now. But I always got the impression that dragging her to America’s foremost museum dedicated to applied mathematics and signals intelligence might not be what she really wanted to do when in our nation’s capital. So I never pushed too hard.

But today my conference took an overly technical turn, and I felt the need to get out early. Two years ago in San Jose I walked around its small cultural district at such quiet moments, finding many pleasant surprises. Last year, I had all of the SOMA and Tenderloin districts in San Francisco to keep me occupied. But very little is around the Raytheon offices in Largo, Maryland, and I didn’t have enough time to go into DC and back up to Baltimore before my flight. So I headed up the Parkway to Fort Meade, the home of the NSA.

I was in Maryland for the HDF and HDF-EOS Workshop X — that’s “X” as in “ten” not “eXtreme.” NASA sponsors the event to encourage usage of the “Hierarchical Data Format” and to share the experiences of data vendors and users. Very, very sexy stuff.

As the EOS name implies, a lot of the data comes from looking at Earth from space via satellites. Some of the science behind these projects has military applications, and some of the data can be “tasked” for various things that people can’t talk to me about and frankly I’m not sure I want to know — who am I kidding, I’m an equal opportunity information connoisseur. The freakier the application the more I want to know. (The best new thing I’ve heard bits about involves looking for nuclear explosions . . . by detecting small, predictable ground deformations . . . from space. Rest assured, I know no classified information.)

So after an enjoyable Wednesday evening sharing stories with the guy from Mitre, the NASA software engineer, the Russian materials scientist, and the businessman, I figured that I needed to see the cryptologic museum if I had the time.

This museum is wierd. Not wierd like the Mütter Museum or charmingly wacky like the National Farm Toy Museum. No this is through-the-looking-glass wierd.

It started on the way to the parking lot as the road passes the NSA headquarters, a large shiny black-box that absorbs information and reflects nothing. It could be any other corporate building except for the barbed wire and cameras and officers and security gates and radio equipment and decomissioned spy planes and the utter spotlessness of it all. The parking lot was just as strange. One bus had middle school students. Another had very well-dressed future bureaucrats about my age. A car from Pennsylvania pulled up and two soldiers in camoflauge piled out.

Inside the door a sign shouts “UNCLEARED FACILITY: NO CLASSIFIED TALK. REMOVE BADGES.” Is this a museum to honor cyphers and decryption gadgets like the Nazi’s Enigma device and the heavy-duty supercomputers that decode your e-mails and harvest the web looking for al-Qaeda plots and (possibly) industrial secrets leaving the country? Or is it a memorial to the hundred-or-so NSA employees (some civilians but mostly military) who sadly died in the service of gathering other people’s secrets? Or is it a cynical attempt to put a shiny face on the NSA? The answer is, of course, “yes” to all of these questions.

The museum has answers but even more secrets. If the most powerful civilian supercomputers top out at over 250,000,000,000,000 operations per second, how much horsepower does the NSA have? (If you must ask why anyone would need that much computing power, it takes a lot of juice to sequence the human genome or simulate a nuclear explosion or find the right words in phone conversations or decrypt secret e-mails.) What information was the USS liberty gathering when it was torpedoed by the Israelis in 1967 off the coast of Egypt? Were the women who ran the cryptanalytic bombes in WWII doing sophisticated work or just spinning dials and feeding papers? (Does it matter?)

“Is this the official museum of the NSA?” The retired-NSA employee who now answers tourist questions thought for an overly long time.

“The NSA runs the museum, so I guess you could say that.” Oh. My. God! There’s another, classified NSA museum “inside the fence.” A few minutes later I overheard him tell someone else that the museum opened in 1993, though the public was only admitted the next year. The very idea of a classified museum just boggles the mind.

In the museum gift shoppe, which was selling NSA Christmas tree ornaments and CryptoKids T-shirts, I asked the clerk whether there was a public walkway to the park containing the surveillance airplanes at the edge of the NSA parking lot. A few minutes later I was standing in the National Vigilance Park after calling Lisa to surprise her that I was at the NSA. She told me to stay out of trouble. (I have a bad habit of taking the wrong turn and getting directions from men with their hands on their sidearms.) I used my cellphone to snap a few pictures of the place. (See next post.)

500+ miles later, at the break in my Perl class this evening, a fellow student and I were talking about his job at General Dynamics. So do you make bombs? “Uh . . . no.” Another overly long pause. Somehow a minute later we were talking about the NSA.

“Did you see the guys with the big guns pointing at you on the exit and the road to the NSA?” What!? No.

“You took pictures of the place? With your mobile phone? You shouldn’t have done that.”

So friends, if I’m not here tomorrow, you know where to start looking. :-) Enjoy the pictures.

Posted in This is who we are, USA | Leave a comment

One down . . .

I submitted my final exam for my Perl class earlier today. I still have a lot to do for my software testing course, but it felt great to finish one class today. Oddly, I have another lecture to attend.

Next: the final exam and project for my testing class. I know what I’ll be doing in the evenings this week in DC. . . .

Posted in Software Engineering | Leave a comment

Oh, Casper, my Casper

Lisa and I are spending Thanksgiving in Casper with my mom and her husband of five years. It’s nice being back in the city of about 50,000 people where I went to high school and spent some summers and vacations during my undergrad days. (I didn’t actually spend a lot of time here as a young’un, but I feel like I “grew up” here, so that’s how I always answer that question.) Since we’re spending Christmas with Lisa’s parents in Oregon, in a couple days the little baby Jesus’s birthday will come, and we will help him open gifts. (Christgiving? Thanksmas? ThanXmas?)

I brought my camera with me — as is my modus operandi — but without any expectation of actually using it. I have a very clear idea how I want to present Massachusetts, but I prefer to travel with an open mind. Looking through the viewfinder forces editing or selecting experiences, and I’m trying to do a lot less of that as I go new places. But Casper isn’t exactly new to me, though every time I return home it feels ever more like déjà vu and less like I actually lived here.

So perhaps it shouldn’t be surprising that while driving home from work on Saturday I started thinking about rephotographic projects of the American West and about the fashion in documentary filmmaking of revisiting the town where one’s parents live in order to understand where we came from and how it has moved on without us and how we’ve diverged from it and how we never really know our parents or our town or . . . you get the idea.

Tuesday, Lisa and I went on my own rephotographic project, visiting the places that were common to me when I lived here: the old house, the houses of my friends, my high school, the Burger King where I used to work, the office where my mother worked and where I helped out, the top of the hospital parking garage. Other places we stopped stuck out in my mind, and I fully expected unmet expectations: I didn’t think there would be a woman in a bikini outside the Tokyo Massage picking up the day’s mail as I saw on my way ot Yellowstone many years ago, for example. (Not today.) Many places were mostly the same with some subtle differences. Banks change ownership. Mini Marts are now Loaf’N Jug stores. Herbo’s (I still have indigestion from eating there in 1992) continues to boast the “worst food and service in town” but is now the “Pork ‘N Bee’s” diner. Others were completely different. Dr. Spokes Cyclery is gone, replaced by a store selling Orvis clothing.

There’s a lot of new development on the east side of town: houses and big box stores. In fact, Casper feels more like other parts of the U.S. now than it did in the past. I can’t tell if downtown is suffering because of these changes or just changing, evolving into a caricature of its past or a stop on the modern trail westward to Yellowstone. New public art downtown suggests surpluses and civic pride, though the defacement of Chief Washakie’s statue suggests some things take longer to change than where people live or shop.

When I get back to the Bay State, we’ll see what develops and I will post photos that probably mean very little for most of you. I know, you can hardly wait.

Posted in Photography, USA | Leave a comment

Annu Palakunnathu Matthew

I haven’t forgotten about my promise to explore contemporary Indian photographers and show what I learn here. Classes are almost over for the semester, and I will be getting back to it. I hope this will tide you over for a while.

“Homeland. But where is home?”

Annu Palakunnathu Matthew‘s work explores (among other things) the expatriot experience. Some of her series include:

Posted in OPP, Photography | 2 Comments

Terry Falke’s “Occupied Wilderness”

I don’t know much about Terry Falke, but he has a new/first book, Observations in an Occupied Wilderness. It’s a contemporary examination of the man-altered landscape.

Posted in OPP, Photography | 2 Comments

Montague / Turner’s Falls

A few weekends ago I visited Leyden and Montague, way up on the Vermont border in West-Central Mass. Turner’s Falls (in Montague) seems an unlikely place for a photography school and an even more unlikely place for an aspiring photography museum, but it has both.

Click for larger

After talking to Lisa and a few other people and reviewing a bunch of my images, I realize that in the Commonwealth project I am exploring (primarily) how humans are situated and interact with the natural environment, particular with respect to development, habitation, and land use. This idea provides a convenient way of tying in the Signs of Nature and High Tension series and also points to some possible ways of organizing the material.

I’m also trying to put evidence of ongoing human interactions into the project to take the edge off the whole post-Apocalyptic, human ruins feel that it — and a lot of contemporary deadpan landscape photography — seems to have.

Posted in Commonwealth Project, Photography | 2 Comments

Small Updates

I was a bit feverish yesterday and today, so I wasn’t able to enjoy the fine weather and continue my Commonwealth project. Instead, I took a look through my files in preparation for the West Newton Cinema show this coming Winter. Imagine my surprise when I discovered that over the last three years I’ve photographed in roughly sixty communities, or roughly a sixth of Massachusetts. Not all of my excursions to these towns have resulted in images that meet my expectations or are coherent with my emerging vision for the project. So, I’ll have to revisit places like Dover, Harvard, and Sudbury; although I like the images very much.

Still, I’m rather pleased with my progress. At last, I have enough images that the project is beginning to feel coherent when I look at 10-20 images, as well as containing several images that are interesting on their own. I’m gradually feeling more hopeful that this wonderful (but long-term) project may prove a success. A few weeks back I talked to an archivist at a local museum, and there’s some enthusiasm.

Now I just need to start working a bit harder, so that I can finish in less than twenty years.

In order to keep you up-to-date in the meantime, I have installed some new photo management and publishing software on my website. It’s rather snazzy but takes some configuring to fit snuggly. So keep watching.

Also, as an international playboy, my interests flit around quite a bit. First a dalliance with this, then a flirtation with that, all bound together by travel and brooding introspection. (The ladies seem to like the brooding badboy.) But if your interests don’t align quite with mine, you may find some of this a bit tedious. So I’m helping you be more selective with more narrow RSS feeds:

Happy reading!

Posted in Always the bridesmaid, Commonwealth Project, General, Photography | Leave a comment

Green Hollow Cemetery, Oakham

Cemeteries not only show who lived and died in a place at a given time. They also show what those people thought about their futures. The Green Hollow Cemetery in very rural Oakham has forty-two graves, although there is space for at least five times as many, easily. But times change, as has where we live and bury our dead.

I won’t list all of the names, mostly Crawfords by birth or marriage. Also Goodales, Fullers, Hubbards, and Fobeses. As I walked around the cemetery, roosters a couple houses over called, and children played in an adjacent yard while their father raked crunching leaves.

  • Lucena Crawford (♂ – 1828-1904)
  • Hubert A. Fuller (♂ – 1865-1868)
  • Lavandar S. Clifford, Apprentice Seaman (†1920)

Update — 30 October 2009: Many thanks to Edie (Crawford) Mathis for correcting my misspelling — it’s “Fobes” not “Forbes” — and for telling me about “a fundraising effort under the auspices of the Oakham Historical Association for the restoration of the Green Hollow arch and improvements to other parts of the cemetery property.” Clearly, there’s some life still surrounding the Green Hollow Cemetery.

Posted in Burying Grounds | Leave a comment

Center Cemetery, Holden

The center of Holden, Mass., contains several choice cemeteries. The small Center Cemetery contains the graves of many widows and officers who served in the “War of 1776.” It’s here that I saw the first revolutionary name: Washington. The gravestones here are in pretty good shape and have some of the best engravings I’ve yet seen. (I really should bring the wee digital camera on these excursions.)

One of the headstones referenced the town of “Midway,” which I had never heard of. It’s possible that they meant Medway — in rural areas misspellings were uncommon but not rare — but over 27 miles separate Holden and Medway as the crow flies. Neither Google nor the Commonwealth’s Secretary of State helped me here. If you know this place, let me know. [1]

Mrs. Betsey Hubbard (♀ – †1822 Æ 32)

As you are now so once was I,
   Rejoicing in my bloom;
As I am now you soon must be
   Dissolving in your tomb.

In Memory of John & James, sons of William & Lucretia Dodd
who died Sept. 18, 1813, both buried in one coffin.
John Æ 2 years & 7 mos, James Æ 9 mos.

Mary, daughter of Samuel & Keziah Damman, Died Aug. 26, 1813, Æ 7 months
“The hand of death, this bud hath nipt, we hope to see it bloom in heaven.

The Dammans had three children who died within 14 months.

Rev. Jos. Davis †1799
“He was the man of Science and a zealous, pungent Preacher.”

  • Olid Combs (♂ – †1813 Æ 14)
  • Widow Persis Mirick (♀ – †1810 Æ 70)
  • Boaz Mirick (♂ – †1809 Æ 27)
  • Col. William Dodd (♂ – †1818 Æ 36)
  • Elmira Nye (♀ – †1825 Æ 20)
  • Amazonia Hubbard (♀ – †1810 Æ 7)
  • Angelinia Hubbard (♀ – †1808 Æ 2)
  • Roxy Flagg (♀ – †1822 Æ 21)
  • Jannat Thompson (♂ – †1744 Æ 77)
  • Mr. Salmon Patridge (♂ – †1827 Æ 35)
  • Nahum Fisk (♂ – †1803 Æ 41)
  • Elnathan Davis (♂ – †1804 Æ 43)
  • Jerusha Chaffin (†1821 Æ 42)
  • Mrs. Abigail Howard, “Relict of Mr. Benja.n Howard” (†1802 Æ 87)
  • Liesy Estabrook (♀ – †1778 Æ 17 mos.)
  • Alpheus Heywood (♂ – †1801 Æ 37)

Update – 5 August 2007: [1] – Yesterday, one of Lisa’s cohort in her choir said that Medway was in fact “Midway” because of its relationship to Medfield and some other town that I didn’t overhear. The mystery is solved yet strangely continues.

Posted in Burying Grounds | Leave a comment

Political Notes

(1) “Now is the time for all good men (and women) to come to the aid of their country.” Be sure to vote tomorrow.

(2) I might actually cast a vote for a winning candidate for major elective office tomorrow — not counting Democrats who run unopposed in the Bay State. If it happens, it would be a first time for me.

  • 1980 President: Jimmy Carter (Dem) — What can I say? I was in kindergarten.
  • 1992 President: GHW Bush (Rep)
  • 1994 Wyoming Governor: Kathy Karpan (Dem)
  • 1994 Wyoming Senate: Mike Sullivan (Dem)
  • 1996 President: Bob Dole (Rep)
  • 1996 Wyoming Senator: Kathy Karpan (Dem)
  • 1996 Wyoming Congress: Pete Maxfield (Dem)
  • 1998 Mass Governor: Scott Harshbarger (Dem)
  • 2000 Democratic primary: Bill Bradley
  • 2000 President: Al Gore (Dem)
  • 2002 Mass Governor: Jill Stein (Green)
  • 2004 Democratic primary: John Edwards
  • 2004 President: John Kerry (Dem)

UPDATE: The curse is over. Deval Patrick won!

(3) I told Lisa that I will no longer vote for John Kerry, as he’s a menace. But, it’s unlikely that I’ll vote Republican any time soon, given who they put into positions of authority and how badly they’ve treated the country recently. So . . . I also floated the idea that if no decides to oppose Kerry in 2008 I will run against him. I’m still fleshing out my platform, but I think “Shut your cake hole, Kerry” would look good on a campaign sign. Please someone, step up and ensure that I don’t have to run.

UPDATE: To clarify, I’m talking about Kerry’s seat in the senate, not his presidential aspirations. (a) As Barack Obama said, “I don’t plan on running for president.” (b) I’m not old enough to be president, yet.

Posted in General, This is who we are | Leave a comment

How a digital camera works

I began this technical article a week ago to synthesize different things I know about the digital camera pipeline and digital image formation. Photographers may be interested in learning what happens after they trip the shutter and before they import it into Photoshop. If you’re not at all technical, you still may enjoy several of the linked articles, some of which show off optical illusions.

How does a digital camera make an image? It seems like such a simple question with a really obvious answer: Light strikes a sensor which converts it to a grid of numbers that is written to a file.

Well, yeah. But how does that grid of numbers (the image) get formed? Recently I helped someone at work answer that question. The result was this chart:

Click for larger

Not every camera does everything the same way. It’s something of a dark art, really. Camera manufacturers do all sorts of secret, proprietary stuff to tweak images. It’s a fact that vendors don’t like to talk about at parties, but, contrary to popular belief, even RAW files don’t contain the raw sensor data. . . . But I’m getting ahead of myself. Let’s look at the various stages in image formation.

Capturing light with a bucket

To be honest, this is the part that I know the least about. There are hardware guys and software guys. I’ve never used a soldering iron and have probably broken Ohm’s Law on a number of occasions. But here’s the important thing to know. In a digital camera, light (energy) strikes a photosensitive material, which induces a current in a circuit attached to the sensor. More brightness, more energy. More energy, more current. Depending on the type of circuitry used, a separate analog-to-digital converter (ADC) turns the current into a count — CCDs need a separate ADC; CMOS sensors don’t.

The current gets counted at each of the millions of “buckets” on the sensor. In order to create a color image from colorful light, you need to break it down into its red, green, and blue components. The eye does this in a very sophisticated way. A camera is much simpler, separating light into three (sometimes four) components via millions of tiny filters, allowing the components to be individually counted.

“It goes up to 11…”

At this point, light has been converted into millions of counts, which range from 0 (no light) to some theoretical maximum. The count depends on the detector’s sensitivity, the ADC, the amount of light, and the color of light. The maximum possible count determines how many individual brightness levels can be recorded. Sensitivity is typically expressed as “bit depth.” An 8-bit sensor can record 256 (2^8) different levels of light. The more bits, the more distinguishable counts.

Bit depth Number of Levels Minimum Value Maximum Value
8 2^8 0 255
10 2^10 0 1023
12 2^12 0 4095
14 2^14 0 16383
16 2^16 0 65535

Not all pixels are created equal. Some buckets on the image sensor are defective and are always on (“hot”) or always off (“dead”). The sensor itself produces heat (“dark noise”), which it detects when recording the scene. And light “leaks” from a sensor before it gets digitized — imagine a bucket brigade that loses a little bit of water with each hand-off. Better sensors have fewer problems.

The result is noise. Sometimes its speckled (so-called “salt and pepper noise”). Often it isn’t uniform across the sensor. In every case, it should be corrected. Hot and dead pixels are averaged with their neighbors (to the dismay of astrophotographers if done on the image data). Another technique known as “dark subtraction” attempts to remove noise by subtracting the heat noise from the exposure. If the dead/hot pixels are known, they can be masked out. Often this happens before the “raw” image is recorded, making it impossible to get the actual sensor data.

Noise disportionately affects the dark parts of the image. Why? Camera sensors experience light differently than we do. If you double the intensity of light (as measured in absolute units, like lux) the light appears twice as bright to a human observer. As a result, when the intensity of light increases, there are larger gaps in sensor counts between equivalent perceptual changes. At the darker end of a scanner’s sensitivity perceived brightness may double every 32 or 64 values; while at the brighter end a similar perceptual change might require 1024 or 2048 levels. (Charles Poynton describes “gamma” in exhaustive detail.) Consequently, small numerical changes make big noise differences in the darker part of the image.

“This ain’t no image, no RGBG

After digitization and noise removal we still don’t have a recognizable image. There’s no color to it yet and the brightness won’t look right either. Remember that millions of red, green, blue, and (sometimes) cyan filters cover the image sensor in order to provide color accuity. Each filter is only sensitive to one color — blue, for example — but if manufacturers use the right pattern for filters, an algorithm can calculate the the other colors (green and red) at the blue filter’s location. The sensor’s pseudo-image is known as a “Bayer pattern.” A “raw” file contains this pseudo-image along with the metadata needed to construct a final image.

Here is a typical color filter array (Bayer) pattern. Don’t blame me if looking at this image makes you have a seizure. If the image appears to be moving or breathing, well, that’s just a result of simultaneous contrast. It’s natural.

A number of different algorithms “demosaic” this pattern data into the RGB image we’re expecting. Typically, speed and accuracy compete to determine the “best” demosaicing pattern. Some algorithms handle images that contain a lot of pronounced edges better than others. In any case, these algorithm look at neighboring pixels to infer the other colors. Collecting these constructed RGB values into separate red, green, and blue color planes (or channels) expands the information content of an image by a factor of three. Adding information to an image post facto almost always involves subjective judgments about image quality.

After demosaicing, the image is more or less what you would expect a color image to look like but probably nowhere near the final state. Remember that the image contains intensity counts at each pixel location, which is not exactly how we experience image brightness or color. The image requires gamma correction and probaly appears dark. In addition, the color balance is probably incorrect, requiring a white point adjustment.

Gamma correction applies a nonlinear power function to the pixel values, making the pixel values match perceived brightness. Often a separate “tone response curve” is applied to each color channel. The power function — which takes larger numbers and creates smaller output values — has the effect of compressing the image’s effective bit-depth (and its dynamic range), as visually redundant information is squeezed out. Some camera vendors, such as Nikon in its D70 model, perform this gamma compression at an earlier stage in order to reduce RAW file size.

It’s not uncommon somewhere in this stage to remap an image’s values from its effective bit-depth to 8-bits or 16-bits. Image processing and image manipulation applications usually need this in order to display the image correctly. Unlike gamma correction, this is typically a linear remapping.

Making pretty images

Tone mapping adjusts the perceived brightness of image pixels but has very little effect on the color balance of those pixels. Several factors determine the color of image pixels:

  • The individual red, green, and blue (R,G,B) pixel values
  • The color of the “pure” red, green, and blue primaries
  • The whitepoint — that is, the color of white

The primaries determine the color of the most saturated red, green, and blue colors that can be recorded or displayed. In an RGB system, every color is a combination of various intensities of these three primaries. If you change one primary’s definition, every other color is changed accordingly. If you’re having trouble with the concept of multiple “pure” red colors being called “red”, just consider what happens when you fiddle with the color controls on your monitor or television set. You aren’t changing the input values that are displayed, but different colors show up on the screen. Different devices have different red, green, and blue sensitivities; and it’s necessary to take the (R,G,B) values from the camera and put them into a well-understood color space where those particular (R,G,B) values have specific color meanings. Some of these color spaces include Adobe RGB (1998), ProPhoto RGB, and sRGB. Industry-wide adoption of ICC color profiles has largely standardized these color translations.

So how does the white point fit in? When you take your camera into a scene with a different color of light, the camera’s color sensitivity doesn’t change. But the human visual system’s sensitivity sure does! Our brains adapt to the scene’s white point, but the camera does not. As a result, the images that we saw and the camera recorded aren’t the same. A simple white point change corrects this problem. (Some cameras have the ability to record the color of the ambient lighting and store it in the RAW file for later use, which is pretty cool if you ask me.)

Digital cameras can store other information in a RAW file — we’ll get to those special files in a second — that help create “good looking” final images. Some cameras store mask information to hide low-quality portions of the image. Any system that samples data into discrete values introduces errors, which often appear as “steppy edges.” Specifying how much chroma blur to add reduces this unwanted effect. (Any image that is blurred — also a result of quanization — probably deserves some sharpening, too.)

Most mid-level and high-end cameras store the Bayer pattern “image” and the hints for reconstructing it in one of the many RAW file formats vendors have defined. Vendors stuff lots of other information there as well, possibly including a lower resolution lossy JPEG thumbnail and EXIF, XMP, and IPTC metadata. Many manufacturers perform lossless compression on the pixels to reduce the size of the RAW file, but this takes time to do. The possibilities and permutations are endless. DNG is a relatively new format whose proponents hope to unify these proprietary formats.

Now go outside and play

I hope you’ve enjoyed this (sort of) brief description of digital image formation and that you now have a better sense of the factors that impact “raw” images. The imaging world is finishing up its amazing transition from film to digital capture, but the image processing tools and digital pipeline are still evolving. Nowadays, knowing what goes into your raw images is akin to knowing how the Zone System impacts film-based photography. If you know of anything that’s out-of-date, please leave a comment.

Posted in Color and Vision, Computing, Fodder for Techno-weenies, Photography | 7 Comments