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Hi TI experts,
I have some questions about NF block concept and tuning.
1. 2 LUTs, Combined LUT and Division LUT are used for NF tuning. Could you help provide examples of these 2 LUTs?
2. I can find 'coeff.txt' in 'psdk_rtos_auto_j7_06_02_00_21\pdk\packages\ti\drv\vhwa\examples\vhwa_nf_test' folder. Could you help explain what it is used for?
3. Concept. According to the formula, I think the basic concept of NF is that 1-D Gauss filter and weighted with intensity difference, which is assumed follow Gauss distribution. Please correct me if I was wrong.
4. Sigma-s and Sigma-c. There are not registers for these 2 parameters. I think I can adjust either or both to generate LUTs then check output image, correct?
Best regards,
Zhishen
Hello Zhishen,
There are two noise filters in VPAC.
My understanding is that you are trying to use BNF. This is OK if you have a YUV coming in from CSI. However, if you are capturing a RAW image and processing it on VISS, I would suggest using NSF4 for noise reduction.
Please confirm which NF you want to use and we can guide you accordingly.
Regards,
Mayank
Hi Mayank,
Please refer to the snapshot below. I mean the Noise filter outside VISS which is in YUV domain.
I plan to use both filters to achieve better de-noise performance. The data flow is raw input to VISS and process through NSF4 in raw domain, then go to Noise Filter in YUV domain.
Best regards,
Zhishen
Thanks for explaining. The folder psdk_rtos_auto_j7_06_02_00_21\pdk\packages\ti\drv\vhwa\examples\vhwa_nf_test is just a low level driver test code which is not used in any application. Currently supported vision apps demos (app_single_cam, app_multi_cam) do not enable NF. Can you please explain how are you running NF?
Hi Mayank,
I didn't run NF yet because I haven't get our target module. Thanks to 'vhwa_nf_test' that I think there is possibility to use NF even without DCC. I plan to apply TI Extension Kernel ( tivxVpacNfBilateralNode) for NF running.
I will come back to you if any problems about my idea and implementation.
Thanks.
Best regards,
Zhishen