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| =Axiom Alpha Prototype=
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| == DNG Converter Software==
| | Please use http://lab.apertus.org instead for task management. |
| * Add other DNG tags such as dead pixels, register settings, black level calibration data, etc.
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| * Implement the matrix as a LUT.
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| * Eventually port to from python to C/C++
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| Code: https://github.com/apertus-open-source-cinema/CMV12000_DNG_Writer
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| ==Linux C/C++ commandline tool to interpret all image sensor registers==
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| We require a c/c++ commandline tool that takes the 128x16bit sensor dump as stdin.
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| Displays the registers in a hex editor like way with addresses and content in a table and next to the table the human readable interpretation of the corresponding sensor parameters (exposure time, etc.)
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| Sensor Datasheet: https://github.com/apertus-open-source-cinema/alpha-hardware/raw/master/Datasheets/datasheet_CMV12000%20v8.pdf
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| Bash script example: [[Axiom_Alpha_Prototype#Reading_and_Writing_Sensor_Register]]
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| ===Notes===
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| * The current memory mapping is 32bit aligned, so the 16bit SPI registers show up as 32bit where only 16bits are significant.
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| * To extract the last 128x16bit from a raw image file use:
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| dd bs=256 skip=98303 if=<file>
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| Or if you have a raw16.xz compressed file you can do it all in one piped command (assuming the c/c++ tool is called "register_info"):
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| xzcat file.raw16.xz | dd bs=256 skip=98303 | register_info
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| * Sample files and format specifications of RAW16 can be found here: [[RAW16]]
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| ==RAW image metadata reader==
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| All sensor registers are embedded into the raw image formats.
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| Details about the file format: [[RAW16]]
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| We need code that can read/display these values in a human readable way.
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| (Similar to the above, but not necessarily targeted at the ARM platform)
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| ==dead/hot pixel detection software==
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| A software that is supplied with several raw images and is able to detect dead/hot pixels and output all detected pixels positions.
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| ==Flat-field correction generation software==
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| A software that is supplied with several (around 20 is sufficient) raw images of an out of focus 30% grey wall and is able to generate the sensitivity offset of each photosite and a resulting flat-field correction matrix (https://en.wikipedia.org/wiki/Flat-field_correction).
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| The samples images are preferably done with a fast 50mm lens stopped down to F4-F5.6 facing an evenly lit surface (white wall with area at decent distance from wall light). To further smooth results the lens should be set to out-of-focus. We need to test if these measurements work even better with a lee filter in front of the sensor instead of a lens.
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