During this time, I had read plenty about noise reduction software but hadn’t really bothered looking into it in any great detail since I had seen what Lightroom’s noise reduction did and it wasn’t impressive. If Adobe couldn’t make a huge difference, surely no-one else would be doing a great deal better so why spend $70 or so on yet another plug-in? As it turns out, however, I was hopelessly wrong.

I’ve spent some time this week playing with a couple of noise reduction plug-ins and am, frankly, gobsmacked at what an amazing job both of these products do at reducing image noise but, more importantly, preserving fine detail. Anyone can get rid of noise by blurring an image enough but these tools get rid of the noise AND keep all my nice sharp edges and tiny details crisp and clean. I have no idea how they manage it but it truly is a wonder to behold!

Topaz DeNoise as seen when launched from within Photoshop (click for larger image)

The first tool I looked at was Topaz DeNoise. I’ve read a lot about Topaz Adjust and seen a lot of great images which use it, but had not heard quite so much about their noise reduction tool. It turned out to be a good find – clean user interface, pretty easy to use and quite a few presets for common noise reduction scenarios. Using it on some of my worst Photomatix images, it did a respectable job of cleaning up the skies without smearing the detail but it did seem to leave some rather odd low frequency artifacts behind. This may have been due to the fact that I was using it without having read the whole manual, I suppose, but in the time I spent playing with the tool, I didn’t get as good a result as I managed to get with the second package I tried.

The user interface of the Noiseware Pro Photoshop plug-in. (click for larger image)

Noiseware from Imagenomic is a piece of software that made my jaw drop. It’s ability to remove noise and clean up an image is almost unbelievable. For HDR, where I am typically keen to remove noise from a sky without affecting other areas, it’s ability to remove noise based on particular colours is fantastic but, even without tweaking any of those sliders, I was stunned by how good a job it did of tidying up my images. I’ve included a couple of examples below showing 100% sections of a particularly noisy image (you can see the original here). I wish I had played with this software a lot earlier since I would have saved many hours masking skies in Photoshop had I known it was so impressive.

Detail before using Noiseware (click for larger version)

Details after using Noiseware (click for larger image)

If you’ve been using this kind of software for a while, you’re probably laughing at me right now but, if you’re not, take some advice from a guy how has wasted a great deal of time trying to solve this problem and treat yourself to a couple of hours with one of these pieces of software. Both are available as free evaluation downloads. Like me, though, I expect you’ll have your credit card out within 5 minutes.

The nice folks over at HDRSoft, the makers of my HDR software of choice, Photomatix Pro, have signed me up for their affiliate program. This is a win-win-win arrangement as far as I can see since all parties benefit – you get a discount, HDRSoft get a sale and I get a commission. I’ve seen several others advertising HDRSoft discount codes but didn’t realise before this week that the arrangement involved a seller commission. In the spirit of full disclosure, though, I thought it would be right to mention this.

If you are buying a copy of Photomatix and use the coupon code “DaveWilson” when you are checking out, you will receive a 15% discount on the purchase, and I will thank you very much.

Despite the mutually beneficial arrangement, I should point out that I have been a huge fan of this software for several years now and, as regular readers will know, have pretty much been acting as an HDRSoft salesman for most of this time!

I’ve always considered myself an early adopter but, thinking about it, I’m actually rather behind the times these days. We are probably the only house in Austin without an HDTV (which is doubly weird given that I used to work in software development for HD satellite and cable settop boxes) and both my computer monitors are still CRTs. My computer, until this weekend, was a rather clunky and extremely unreliable HP system running Windows XP on a dual-core AMD Athlon 64. Much as I love Adobe Lightroom 2, running it felt very similar to wading through syrup.

Things changed this week, though. In anticipation of my upcoming expedition to Utah and in celebration of the start of a new tax year, I’ve bought my first laptop and fully intend this to become my main digital darkroom machine with the HP relegated to the role of file and print server. The new machine is a Dell Studio XPS 16 with a Core2Duo CPU, 6MB L2 cache, 7200rpm hard disk, upgraded graphics card and 64 bit Windows 7. It’s an absolute screamer (for a Windows machine)!

I’ve installed 64 bit versions of all my software where these versions are available. Lightroom 2, Lightroom 3 Beta, Photoshop CS4 and Photomatix Pro 3.2 all come in “double-wide” versions and the performance difference compared to my old machine is staggering. Lightroom exports happen in a very small number of seconds and, even more impressively, I can view the effects of slider changes in the Develop module in real time! No more “move the slider, wait for the effect”!

Couple this superb performance with the fact that the display is absolutely gorgeous (allegedly having a colour gamut encompassing the whole AdobeRGB space) and I’m definitely enjoying this as my new mobile office.

Oh, I almost forgot – it’s red too.

Edit: A more knowledgeable colleague just pointed out that the Keanu PSA was actually prepared for last year’s competition. That answers my question about why it doesn’t contain any footage from the 2009 competition. Oh well…

The issue under discussion related to the relationship between the number of bits used to store a High Dynamic Range image and the light levels that the image can store. An HDR image is typically thought of as being represented with 32 bits per color component (32 bits of red, 32 bits of green and 32 bits of blue for every pixel). Some of the most common HDR file formats actually use less than 32 bits per pixel but, regardless, the question comes up about what each of those bits represents and how the number of bits dictates whether an image is “High Dynamic Range” or not.

I had always assumed that the dynamic range of an image depended to some extent on the absolute maximum light level that could be recorded. On reading Christian Bloch’s rather good “HDRI Handbook” last year, I was surprised, however, to read that the dynamic range is defined instead in terms of the ratio of the number of discrete values (2**32, for example if we’re talking about a 32 bit number) a measurement can represent divided by the smallest measurable difference (the change in the signal represented by 1 least significant bit). Nowhere in this calculation does any absolute value appear – the dynamic range is a ratio of the largest and smallest values that can be represented but it says nothing about the actual quantities that those values represent.

This didn’t seem intuitive to me. Where was the reference? How would you know how bright a given pixel would be? Thinking about this for a while, however, it became clear that I was forgetting to take into account the camera as a whole rather than merely the sensor.

The camera’s sensor has a fixed, maximum signal that it can record and a certain number of bits of resolution. For example, a 12-bit sensor can differentiate between 2**12 (of 4096) different levels of red, green and blue light. At some absolute level of light, the sensor saturates and outputs its maximum value. If you increase the light level falling on the sensor above this amount either by keeping the sensor exposed to the light for longer or by increasing the brightness of the light falling on the sensor, you get no new information and the signal stays saturated.

Thinking about this from a photography point of view, however, this is exactly as you would expect and corresponds to overexposure. In this case, we close the aperture, reducing the brightness falling on the sensor, or speed up the shutter to reduce the total amount of time the sensor is exposed to the light. These changes reduce the total amount of light falling on the sensor and allow us to take another, hopefully correctly exposed image. Although the maximum light level the sensor sees has dropped and it no longer saturates, it still records 4096 different levels falling on it. The recorded dynamic range is the same but we’ve shifted the recorded values so that all of the actual image brightness levels fall within the recording capabilities of the sensor.

This is exactly as you would expect in a film camera too – if the film is overexposed, it “saturates” to opaque and you can’t store any more information (there is the complication of logarithmic vs. linear response here but let’s gloss over that for now since it’s not really relevant to this discussion). In these cases, you reduce your exposure to get the amount of light hitting the film such that you don’t saturate the medium.

Considering things this way, it is now clear (to me at least) that the absolute value of light represented by the sensor’s (or film’s) maximum output value is irrelevant. The photographer adjusts the exposure to ensure that the brightest highlight in the image is at or just below the sensor’s saturation point and, hey presto, you end up taking maximum advantage of the sensor’s dynamic range. The absolute maximum light level that will cause the sensor to saturate is, therefore, related to the sensitivity and not the dynamic range. If the sensor saturates with very little light hitting it, we end up with a high sensitivity (or high ISO) sensor that allows us to record images in lower light than one which saturates at higher light levels.

So how does this tie back in to the normal photographic system of defining exposure in terms of stops or EVs? For every bit you add to a sensor, the number of values it can represent doubles and, as a result, its theoretical dynamic range will also double (forgetting about noise which reduces this somewhat). Thinking about exposure calculations, you know that increasing your exposure by a stop also doubles the amount of light hitting the sensor. There is, therefore, a direct correlation between 1 stop and 1 bit. Reducing your exposure by a stop divides the sensor output in two or shifts the value one bit to the right. Adding a stop to your exposure does the opposite, doubling the sensor output or shifting the value one place to the left.

Using the bit shifting idea, we can, therefore, get some idea of how much dynamic range an HDR image may have based upon how we recorded it. I typically use 3 images bracketed 2 stops apart when shooting HDRs. If the original scene contains very bright highlights or lots of dark shadow areas, I will use more brackets but 3 is usually enough. My Nikon D90 has a 12 bit sensor and, at low ISO values, has close to .12 bits or 4096 levels of dynamic range. Adding +2 stops to the exposure has the effect of multiplying the sensor output values by 2**2 or 4 or shifting them 2 bits to the left. Taking away 2 stops has the opposite effect, dividing the output values by 4 or shifting them 2 bits to the right. When I combine all three exposures, -2 stops, 0 stops, +2 stops, into an HDR image, therefore, the maximum dynamic range I could possibly record would be 12 + 2 + 2 bits or 16 bits of information. Even though I may save this image in a 32 bit file format, I’m not actually storing pixel values that extend from the lowest to the highest possible value in the file format. Regardless of the fact that I’m not using the full dynamic range of the recording system (the 32 bit pixel component representation), I still have 16 bits of information per colour component which is twice the number of bits I would have had if I had saved in JPEG and 4 bits (or 16 times) more than I would have got from a single RAW file from the camera. The dynamic range of my image is something like 65536:1 versus 256:1 for JPEG or 4096:1 for my 12 bit RAW format.

Confused? If so, leave a comment and I’ll try to clarify this a bit!

The downside of this, of course, is that flights are no longer an opportunity to read, play games or generally do non-work things (like post to blogs?) during work time. I guess I had better get back to the email….

This morning, my 6 year old son introduced me to some videos on YouTube that give a whole new meaning to audio/video synchronisation. These animations do a superb job of synchronising the animated video content with the soundtrack. They are completely mesmerising. Take a look at this one then head over to YouTube for various others. You can buy DVDs at www.animusic.com.

“Flickr è la migliore applicazione per la gestione e la condivisione di foto online. Se sei curioso di sapere per che cosa lo utilizzo, guarda il mio profilo oppure naviga tra il mio album.”

…and the web site translated this as:

“Flickr is the best application for the management and the sharing of photo online. If you are curious of knowing for I use it what, watches my profile or is annoying between my egg whites.”

I do find unsolicited messages like this rather annoying (though I think this was the first example of Flickr spam I have seen) but, in this case, it ended up having great entertainment value and didn’t disturb my egg whites at all.

Setting the service up on my photoblog was trivially simple. After logging on to the Fotomoto site and setting pricing for the various print sizes, I copied a small block of JavaScript and pasted it into the footer of the photoblog page. Immediately, all the images have a couple of new, unobtrusive links added beneath them, one to allow print purchases and the other offering to send an eCard containing the image.

Some of my images were taken in places which do not allow commercial sale of photographs taken there and one was taken with an old digital camera whose resolution was not really up to producing high quality prints so I had to return to the Fotomoto control panel to indicate which images were not for sale. Overall, the installation and customisation was incredibly easy.

So far, this looks as if it should be a superb service. I’ll purchase a couple of test prints and report back once I have checked out the print quality. Assuming it’s on a par with ImageKind, I will likely move all my online print purchasing there since FotoMoto do not charge an annual fee (they take a 15% commission on each sale instead which, given my current sales volume, works out better for me)

Some Examples of Good HDR

Photographic tastes are very personal but, to get things started, I would recommend looking through the work of some of these folks who I think do a fantastic job of showing HDR techniques used extremely well. I would be foolish to suggest that these are the best HDR photographers on Flickr but they are certainly the ones whose work I follow closely and very much enjoy. These are in no particular order.

• Trey Ratcliff (stuckincustoms) is probably known by many as the king of HDR. He travels extensively and posts new photos daily. His blog is also well worth following and is a great place to start if you are looking for an HDR tutorial.
• ~EvidencE~ (who doesn’t provide a real name) posts wonderful examples of HDR depicting industrial scenes and decay, in addition to some superb landscapes.
• Roman Solowiej (shexbeer) also concentrates on images of decay and destruction where HDR techniques are used to great effect to accentuate texture.
• Karl Williams (Shuggie!!) takes wonderful urban and landscape images using HDR techniques for the majority of his pictures. Many of Karl’s images are taken around my old stamping grounds in Glasgow, Scotland.
• Erlend Robaye (Erroba) produces beautiful citiscapes and abstracts using HDR techniques.
• Jerry Hayes (JerryHayesAustin) is a local photographer with whom I have had the pleasure of shooting a few times. I’m linking to his set of Special Event Photography images since these are fabulous examples of how HDR can be used subtly to produce natural looking results in tricky lighting situations.
• Steve Sawford (Steel Steve) is another UK-based photographer whose urban HDRs taken in the industrial north of England are superb.
• Raul Pires Coelho (raul_pc) is based in Portugal but posts urban and cityscape HDRs from around Europe.
• Sarah Peters (sarah_peters1) is based in the town of Douglas in Scotland (9 miles from my home town, as it happens) and uses HDR techniques on many of her stunning landscape shots. Again, her images show wonderful use of HDR to produce natural-looking results.

Books

There are loads of web-based resources for learning HDR but I find having a good old fashioned book a great way to learn. Here are three that I particularly like.

• “The HDRI Handbook” – Christian Bloch. I found this book extremely helpful but it would probably be better read after having worked with HDR for a while since it covers a fair bit of theory. It does a great job of comparing software tools and also comes with a CD containing various images and evaluation copies of some of the tools.
• “The Complete Guide to High Dynamic Range Digital Photography” – Ferrell McCollough. I’ve just bought this book and have not yet had a chance to read it through. From what I have seen, however, it looks to be a very practical guide and probably a great book to read as someone wanting to start shooting HDR images.
• “Mastering HDR Photography” – Michael Freeman. I picked this book up and had a look through it in our local book store recently and was very impressed. It covers a lot of ground and has a very good mix of technical and practical information.

Software

I use a combination of Adobe Lightroom 2, Adobe Photoshop CS3 and HDRSoft Photomatix to produce my HDR images. You can do the vast majority of the work in Photomatix alone but I find that Photoshop does a better job of merging images if there is any movement between the exposures and I feel that I get better images if I use the Photomatix export filter for Lightroom rather than loading the raw NEF files directly into Photomatix . Regardless of which tool I use to generate the HDR file, I always use Photomatix for my tone mapping. HDRSoft offer an evaluation version of Photomatix which watermarks its output and also a useful tutorial to get you started. The tool itself costs $99 but if you use coupon code “DaveWilson” when you are checking out, you will get a 15% discount.

Another tool I have played with briefly is Ariea HDR Max. This has a more polished user interface than Photomatix and one feature that I really like – the ability to turn on and off the contribution of any single exposure to the final HDR. That said, I found the tone mapping settings less flexible than Photomatix and had trouble especially with the gamma slider which seemed to generate enormous changes in the image with tiny movements. This may be fixed now and I would encourage you to download this trial version too to see how you like it.

I also have FDRTools on my “must check this out” list. I’ve seen some superb images created using this software but have yet to download the trial and play with it. The package is very inexpensive and endorsed by some of the big names in the HDR world so it’s definitely worth a look too.

Many, many other freeware and commercial tools exist to generate HDRs and tone map them so try as many as you can and settle on whichever gives you results you are happiest with.

The FIRST (For Inspiration and Recognition of Science and Technology) organisation was founded by Dean Kamen (of Segway fame) to “transform our culture by creating a world where science and technology are celebrated and where young people dream of becoming science and technology heroes.” and, as far as I can see, it is doing an outstanding job. The competitive side of the program is completely secondary – yes, you get to compete against 60 or so other teams at a regional like this but the really important part of being there is to meet the other teams, exchange ideas and help out the rookies (and anyone else needing material or expertise that you can provide). They call it “coopetition” and it breed a wonderful atmosphere at the events. The program strives to promote “gracious professionalism” where competitors respect each other and chest slapping and victory dances are definitely not allowed.

I had a whale of a time at the competition and will definitely be looking for more ways to stay involved with FIRST. If you have an interesting in promoting science and technology in education, you could do a great deal worse than check these folks out.

Here are a few snaps to give you a feel for the event. I should point out that the game the robots were designed for involves getting balls into trailers towed behind your opponents.

This is the second time in a couple of years that I’ve had something like this happen resulting in site downtime. The blog has been powered by pMachine which, although easy to use, apparently has some security holes. Unfortunately, it is no longer supported so I think it’s time for me to migrate to WordPress instead. As a result, you may see some changes and a lack of posts for a few days while I get the new code installed and figure out how to migrate the existing posts between the two systems.

Wish me luck!

(This entry was actually posted on the old blog before the “Pardon our dust” but got out of order thanks to a time zone error on the old blog. Apologies for any confusion!)

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Falkirk Wheel in motion 2 (mono), originally uploaded by David A G Wilson.

It’s a funny old (search engine) world. Scanning through my Flickr referrer stats today, I happened to take a look at the search engine terms that resulted in hits to this image. If you are suffering glandular fever (or mononucleosis as it’s known in the US, affectionately abbreviated to “mono”), you may be surprised to see this image pop up in the top 10 if you search Google images for “treatments for mono“. It’s the only image completely unrelated to the disease on the first page.