Interview with photogrammetry expert Barry Bassnett

Barry Bassnett (Shadow Buster) - 32-bit photogrammetry expert

Barry Bassnett

Photogrammetry, the process of making measurements from photographs, has become a powerful tool in various fields, from drone inspection to cultural heritage.

Barry Bassnet is a photogrammetrist with decades of experience and a renowned authority in the industry. He also has been advocating the use of High Dynamic Range (HDR) imaging techniques to improve the quality of the input photos used in the photogrammetry process.

We invited Barry to chat with us. The questions discussed are listed below, followed by a summary of the interview.

Interview summary

What is your background and how did you get into photogrammetry?

Barry discovered his passion for photography at a young age, recalling, "I've been photographing since the age of 12... photography sort of got my attention". He spent his teen years with a single lens reflex camera doing his own developing, dodging and burning, and similar.

He then began a career as a cartographer with Ordnance Survey, where he learned the critical role precision survey control plays in getting good results.

Later, Barry delved into close-range photogrammetry, working with companies such as British Aerospace, Boeing, Volkswagen, and Volvo to photograph and model objects like aircraft jigs, car bodies, machine tools, and pipe work, in some cases requiring precision down to one tenth of a millimeter.

Another perhaps surprising industry he learned a lot that carried over to photogrammetry was in film, doing HDRI (High Dyanamic Range Image) capture and working with Visual Effects companies to engineer light.

What aspect of photogrammetry do you enjoy most? Which do you find the most challenging?

Barry’s favorite aspect of photogrammetry is undoubtedly making sure he gets the proper image quality. He says "that's really the basis and fundamental bit of the photogrammetric process".

He emphasized the significance of capturing high-quality images, highlighting the satisfaction he gets from initially capturing the photos that are going to give him the results that he’s looking for, and thinking about how to get the most out of every pixel.

One of the biggest challenges in photogrammetry is capturing the scene in a way that will produce the desired results in the end. Some places are far easier to shoot than others, simply due to the amount of light they get.

Some applications of photogrammetry require a neutral model without shadows and highlights already in the image, so it can be lit afterwards. Barry tells us that somewhere like the west coast of Scotland with overcast weather is perfect for this, but capturing a telecoms tower in Texas is a whole different matter.

The challenge, then, is the intellectual puzzle of figuring out how to process the image long before even getting to the software that will render the source photos the final results, which can only be as good as the images that are fed into the software.

Barry asks himself “How do I make the image the best quality I can, so that it doesn’t impact the accuracy of the modeling or compromise the textures”.

What got you interested in HDR techniques and when did you first explore their use for photogrammetry?

Barry’s interest in HDR imaging techniques came about when he discovered the .EXR file format, which was well before he entered the CGI industry. He was immediately fascinated by its potential to revolutionize photogrammetry and his own workflow.

The tools that existed before were great for processing single images, but he needed to process hundreds or even thousands of images and apply the same changes across them all. The EXR format was perfect to allow him to play with the data of each individual pixel.

Barry agrees that it would be fair to say that the file format itself is what led him to exploring HDR and all its practical applications for photogrammetry.

HDR techniques have been invaluable for him in capturing details in challenging lighting conditions, preserving the full range of information ranging from bright sunlight to deep shadows.

Could you give an example where merging exposures to 32-bit HDR improved the result?

Barry narrows them down to two situations that stand out the most where using 32-bit images gives notably improved results over a single exposure 8- or 16-bit image.

For the first, he gives an example, "Where it’s dark.. a railway in the country where it’s unlit and you haven't got task lighting to be able to produce daylight quality imagery". With exposure bracketing in such a scenario, it works like magic to create an end result that is still inspection quality.

On the other end of the lighting spectrum, he mentions using the technique for telecom mast inspection in bright sunlight, stating, "Those boxes are white or black, I can't see what the texture is and the condition is, then suddenly you can bring that out... that's where the whole HDR/32-bit experience comes into its own".

By leveraging HDR and merging bracketed exposures, the texture and quality of the images are significantly enhanced, providing a more comprehensive and accurate representation of the subject.

What made you choose the term 32-bit photogrammetry to refer to the use of HDR in photogrammetry?

Barry prefers the term 32-bit over HDR, and he explained a few reasons for this.

The first is that the term HDR has been hijacked and is now often used to describe high resolution or high definition. One example he cites is that “You get HDR-ready television… well, that's that's got nothing to do with light, it is to do with their resolution so a lot of people get confused with that”.

The second is that HDR has gone through artistic phases and sometimes leads to exaggerated and unnatural images. Barry states, "I want it as natural as possible. I'm trying to recover data I’m so not really interested in the aesthetic quality of the image. I'm more interested in recovering every single bit of data that I can".

The misconception of what HDR means could result in people misunderstanding the benefit of using 32-bit imagery.

Finally, using the term 32-bit helps to separate it from LDR (low dynamic range) and emphasizes the greater control and detail obtained. He takes a very small part of the adjustments available and focuses on using them for the type of data recovery that just isn’t possible with an LDR image.

What are the photogrammetry applications you think could benefit the most from 32-bit/HDR?

Barry also sees a wide range of places that 32-bit/HDR imagery can be useful. Some of the ones he thinks are more obvious applications are heritage archiving, insurance, and academic research.

Crime scene forensics and other forensic photography can also greatly benefit from these techniques. He suggests things like “capturing crime scenes at night or in bright sun... using the HDR bracketed image to stitch together a 360 image… combining things like focus stacking with HDR, you can actually enrich the whole process".

Generally speaking, the use of 32-bit in photogrammetry can vastly improve results by providing accurate representation, true color reproduction, and the ability to recover detailed information from the captured images.

What are your top 3 tips you would give to people starting out in the photogrammetry industry today?

Barry is full of useful advise for someone who is getting started in photogrammetry, but narrowed it down to three key tips that will set one up for success.

Tip 1: Understand your camera

"Your camera is your friend. Understand completely how the system works and hold in your hand all the time. Knowing its defects, its lenses, and its capabilities by making it an extension of yourself will allow you to consistently capture the quality of information you need.

Tip 2: Understand how light works

"I would spend a bit of time looking at the whole HDRI process, and probably spend some time looking at Maya or Blender and the workflow. It will give you a really good understanding of light and what you're doing."

Tip 3: Work slower

In this age of instant gratification, Barry thinks it's easy to rush through capturing images, but taking your time allows you to focus on quality and attention to detail.

"Because I'm normally looking at longer exposure times, I'm always using a tripod. It forces me to slow down and frame things exactly as I want to. Maybe it's not as productive, but it's all about quality imagery, thinking about getting the focus right and depth of field."

What excites you the most in the technological developments in the photogrammetry industry?

There are a lot of technological developments happening in the photogrammetry industry, and Barry finds joy and excitement in a lot of it. When asked, he said, "Every day, it's like starting my career again because something new happens".

He’s really glad to see that photogrammetry is becoming more of a mainstream thing outside of geomatics, and finding it’s way in the hands of more people so they can capture heritage and preserve it forever.

Barry also recognizes the role that AI will play in changing photogrammetry. He sees AI enhancing image quality and enabling advanced analysis techniques.

Looking ahead, Barry envisions a future where photogrammetry merges with technologies like LiDAR and Universal Scene Descriptors. This combination will enable immersive experiences and create a virtual world akin to HTML. He eagerly anticipates this development, saying, "We will be able to copy and paste experiences and objects... it's going to be the HTML for the virtual world".

AI and machine learning are already revolutionizing photography. AI tools built into applications like Adobe's Lightroom and Photoshop are already used for post processing, doing things like identifying and enhancing specific areas of an image, such as shadows. Barry believes that AI editing tools are becoming increasingly valuable in improving image quality.

AI also aids in image analysis, with applications ranging from aesthetics to identifying cracks in runways. While no single program excels in all aspects, integration and advancements in AI are certainly improving every day.

When it comes to photogrammetry, Barry acknowledges that the process still involves time-consuming manual tasks. However, he sees AI playing a significant role in making the photogrammetry process more efficient.

He mentions the use of AI algorithms and machine learning in photogrammetry software, which can automate various steps, including point matching clouds and generating 3D models. However, it’s important to always remember that while AI can improve efficiency, the quality of the data remains crucial for accurate results.

At the end of the day, Barry says, "AI is going to allow more and more people to capture and share their environment and their experience, and that has to be a good thing".

More information about Barry Bassnett, and photogrammetry can be found at his RICHPiX website at

Barry offers courses in Photography for Heritage Documentation, Structural Inspection, and Reality Capture.