What is fine resolution?
The technology used to enhance the resolution of a digital
image is known as super resolution. Over the course of digital imaging system
development, many different techniques of super resolution have been developed;
each with its advantages and disadvantages. A thermal imaging system
assimilates the resolution enhancement technology used in digital imaging
system to improve on its resolution. The TrueIR thermal imager uses a
specific multi-frame super resolution technique and algorithms that is known as
fine resolution, which enhances the resolution of a thermal image by four
times.
So what is fine resolution and how does it work?
It can be summarized to 3 main processes – Acquisition, Super-position,
Reconstruction.
Each of the above mentioned processes have different tasks
on its own.
Acquisition:
Whenever the trigger button is pressed, the thermal imager
will automatically capture multiple images of the same scene continuously. It
also assumes that each of the images or frames taken is shifted, due to natural
hand movement of the thermographer. Also, during the acquisition, all the
frames are automatically up-scaled to higher resolution images through
interpolation technique – predicting image pixels using data from adjacent
pixels that has been captured initially. The technique is very similar to a curve
fitting mathematic function. The new pixels are predictive values instead of
measured values.
The interpolation process is fast, hence, the high
resolution interpolated images are real time. Instead of showing the real time
low resolution image on the display, the interpolated high resolution images
are displayed on the LCD, which serves as a view finder for the thermal image,
just like a digital camera.
Super-Position:
As mentioned, each of the frames taken through multi-frame
acquisition process is slightly shifted. Therefore, overlapping the frames
without any intelligence will not work. In this process, feature points from
each of the frames needs to be identified, positioned and aligned together
before being superimposed to form a high resolution image. Figure 1 below illustrates this process.
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Figure 1: Super-position |
Reconstruction:
Superposition process above might incur some
noise into the thermal image, causing it to be fuzzy. Hence, at this stage, many
mathematical models and image processing techniques are used, such as an averaging
algorithm for noise reductions and an edge enhancement algorithm for image
sharpening.
The Result:
Here’s a simple lab test to prove the point. We simply
measure the temperature of a slim 1-mm vertival bar at a fixed distance. Figure 2 illustrates the ability of the TrueIR detector’s array to capture the thermal image of the slim bar. Due to limitation of the physical iFOV discussed earlier, if a single frame is used (in this example that means only Frame 1 is used), only the average temperature of the bar is recorded, which is inaccurate.
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Figure 2: Detector's pixel arrays |
Through multi-frame acquisitions, Fine Resolution is able to recover sub-pixel information. Figure 3 shows the test result comparison between using a detector with 160 x 120 pixels versus the results obtained using a fine resolution imager which generates an image with 320 x 240 pixels. Fine resolution provides 1.5x better iFOV, thus resulting in 1.5x more accurate temperature measurement. So you get to reap the benefit of a 320 x 240 pixels thermal
imager for just a fraction of the cost!
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Figure 3: Lab test resuts (1-mm bar) |
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Sample Fine Resolution IR images taken with Keysight's U5855A TrueIR thermal imager |
To
read more about Fine Resolution capability, click here.
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The U5855A TrueIR thermal imager |