Image Clarity: What to look for

We all know that seeing the details is critical in a fire scene. For years, when it comes to image quality in thermal imagers, much of the discussion has centered around image resolution. While image resolution is important in thermal imaging, new technology has made it possible to process images in an advanced manner that brings greater resolution detail.

It’s all about image processing.

These days, image processing is where all the magic happens in thermal imaging. Image processing is actually a very technical activity. During image processing, the engine core of the camera (the “brains”) takes the signal it receives from the camera sensor and converts it into an image.

High gain or low gain? And what does that really mean?

Images can be processed in lower gain modes or higher gain modes. The “gain” is essentially the level of sensitivity. Just as with a radio, an infrared detector must adjust its gain level to filter out background noise. Some thermal imagers process the entire scene in either a high gain mode or low gain mode. This works fine except in instances where a firefighter needs to see the detail of lower temperature items (like people or egress points) in the same field of vision as a raging fire.

The environment in a fire makes image processing difficult.

That’s why the best processing must be pretty complex.

In the same way that a bright sun can obscure the details in a photographic camera, the gain mode required to process the thermal image of a hot fire reduces the detail of other items within the same scene.

To overcome that, new processing techniques available in some thermal imagers apply something called Adaptive Rescaling. Here’s what that means:

Behind the scenes, the image is instantly broken down into three spatial frequencies that independently process in high, mid, and low gain modes, depending on the needs of that part of the image.

This allows the camera to immediately process the image of very hot items and cooler items within the same scene, without losing the image details. Adaptive Rescaling allows firefighters to see details that have previously been obscured.

Focusing on the details.

In addition to the gain mode in which the image is processed, there are other ways to help firefighters see the details in a fire scene. The camera’s engine core can bring out the edges of objects, as compared to the background of the image. This is basically sharpening the image.

Another processing technique that can be applied is Dynamic Contrast Thresholding. This process definitely is as complex as the name sounds. Ultimately, the engine core isolates the most significant image content in the scene and applies special image processing to that portion of the scene to instantly boost the image contrast in that area.

You don’t necessarily have to understand the science. You’ll know it when you see it.

The elements that make an image clear are complex and varied. It’s not as clear-cut as comparing the specs on resolution. However, the difference in image quality is evident when cameras are compared side by side in a re scene. The best thermal imagers are designed with an eye to balancing each of the image processing elements mentioned above with good resolution and high quality displays.

Where does resolution come into play?

Resolution is the number of pixels per unit of area. In theory, with more pixels available per area comes the capacity to show greater detail. However, that clarity is limited to the amount of detail the image processing can translate into pixels. That’s why greater thermal imaging resolution can only create a clearer image when partnered with advanced image processing.

What to look for? Balance.

When evaluating thermal imagers for image clarity, you’ll want to look for a design that has balanced the image processing, resolution, and brightness of display to create an image clarity that reveals the details your fellow firefighters will need to see to make critical decisions during a re. It’s definitely a balance you’ll recognize when you evaluate an imager design that gets image clarity right.

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