Test Images; Ramp; Lfsr; Troubleshooting Using The Lfsr - Photon Focus Gpixel MV8 Series User Manual

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11 Pixel Data Processing

11.8 Test Images

Test images are generated in the camera FPGA, independent of the image sensor. They can be
used to check the transmission path from the camera to the acquisition software. Independent
from the configured grey level resolution, every possible grey level appears the same number
of times in a test image. Therefore, the histogram of the received image must be flat.
A test image is a useful tool to find data transmission errors or errors in the access
of the image buffers by the acquisition software.
The analysis of the test images with a histogram tool gives gives a flat histogram
only if the image width is a multiple of 1024 (in 10 bit mode) or 256 (in 8 bit
mode).

11.8.1 Ramp

Depending on the configured grey level resolution, the ramp test image outputs a constant
pattern with increasing grey level from the left to the right side (see Fig. 11.13).
Figure 11.13: Ramp test images: 8 bit output (left), 10 bit output (right)

11.8.2 LFSR

The LFSR (Linear Feedback Shift Register) test image outputs a constant pattern with a
pseudo-random grey level sequence containing every possible grey level that is repeated for
every row. The LFSR test pattern was chosen because it leads to a very high data toggling rate,
which stresses the interface electronic and the cable connection.
In the histogram you can see that the number of pixels of all grey values are the same.
Please refer to application note [AN026] for the calculation and the values of the LFSR test
image.

11.8.3 Troubleshooting using the LFSR

To control the quality of your complete imaging system enable the LFSR mode, set the camera
window to 1024 x 1024 pixels (x=0 and y=0) and check the histogram. The camera window can
also be set to a multiple of this resolution (e.g. 2048 x 2048 or 4096 x 3072) if the camera
model supports this resolution. If your image acquisition application does not provide a
real-time histogram, store the image and use an image viewing tool (e.g. ImageJ) to display
the histogram.
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MAN094 02/2022 V1.1

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