Note
• An NUC update is recommended any time an adjustment is made to either the frame
rate or the integration time, regardless of the integration mode.
• The IWR mode is not available in all camera models.
8.5.2
The ITR process
As seen in Figure 8.3, the frame generation process begins with a frame synchronization
(Frame Sync). The camera then integrates the set amount of time, goes through a fixed
dead time, transmits data, goes through a second fixed dead time, and then is ready to
start the process over again. The figure shows that the camera first completes the inte-
gration process and then reads the data out, hence the term “integrate then read.”
Figure 8.3
The ITR frame generation process.
All timings for the frame generation process are based on a 50 MHz clock, yielding a res-
olution of 160 ns. The minimum integration time for the FLIR X6530sc is two clock cycles
or 320 ns.
Table 8.1 gives the method for computing the maximum frame rate for the ITR process.
Table 8.1
ITR maximum frame rate calculations
Data width
[8 + number of c number of columns ×
number of rows)]/50 M
Dead time
246.32 µs
Integration time
User defined; [320 ns ≤ integration time ≤ 11
minutes]
Frame rate
1/[integration time + data width + dead time]
Table 8.2 shows the ITR calculations for a typical frame setting of 640 × 512 with an inte-
gration period of 2.0 ms.
Table 8.2
ITR maximum frame rate calculations, 640 × 512, 2.0 ms integration time
Data width
[8 + 640 + 640 × 512]/50 M = 0.006566
Dead time
246.32 µs
Integration time
0.002
Frame rate
1 / [0. 0. 00 0.002] = 1/
[0.0088129] = 113.47
8.5.3
The IWR process
The integration and the data readout periods can be thought of as two separate proc-
esses. However, they are linked by certain timing requirements. This means that the
camera can integrate for a period, then starts the data readout for that integration period,
and during that readout starts the integration period for the next frame. This process is
thus termed “integrate while read,” and can greatly speed up frame rates, as seen in Fig-
ure 8.4. The drawback to this process is that it injects a fixed pattern noise into the data,
which can be removed by performing an NUC on the data.
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