Commit b97d4a1e authored by Mauro Carvalho Chehab's avatar Mauro Carvalho Chehab
Browse files

media: docs: ipu3.rst: rely at automarkup extension 



There are several :c:type: definitions there, in order to
do cross-references with the driver's documentation.

Those are broken when docs are built with Sphinx 3.x, as
it would require :c:struct: instead.

For Sphinx < 3.x, the automarkup.py extension is able to do the
replacement already, and a future improvement on it should make
it also work with Sphinx 3.x.

So, get rid of the usage of the :c:type: macro there.

Reviewed-by: default avatarSakari Ailus <sakari.ailus@linux.intel.com>
Signed-off-by: default avatarMauro Carvalho Chehab <mchehab+huawei@kernel.org>
parent 1c16b009

Documentation/admin-guide/media/ipu3.rst

+19 −19
Original line number Diff line number Diff line
@@ -488,63 +488,63 @@ Name Description 
Optical Black Correction Optical Black Correction block subtracts a pre-defined

			 value from the respective pixel values to obtain better

			 image quality.

			 Defined in :c:type:`ipu3_uapi_obgrid_param`.

			 Defined in struct ipu3_uapi_obgrid_param.

Linearization		 This algo block uses linearization parameters to

			 address non-linearity sensor effects. The Lookup table

			 table is defined in

			 :c:type:`ipu3_uapi_isp_lin_vmem_params`.

			 struct ipu3_uapi_isp_lin_vmem_params.

SHD			 Lens shading correction is used to correct spatial

			 non-uniformity of the pixel response due to optical

			 lens shading. This is done by applying a different gain

			 for each pixel. The gain, black level etc are

			 configured in :c:type:`ipu3_uapi_shd_config_static`.

			 configured in struct ipu3_uapi_shd_config_static.

BNR			 Bayer noise reduction block removes image noise by

			 applying a bilateral filter.

			 See :c:type:`ipu3_uapi_bnr_static_config` for details.

			 See struct ipu3_uapi_bnr_static_config for details.

ANR			 Advanced Noise Reduction is a block based algorithm

			 that performs noise reduction in the Bayer domain. The

			 convolution matrix etc can be found in

			 :c:type:`ipu3_uapi_anr_config`.

			 struct ipu3_uapi_anr_config.

DM			 Demosaicing converts raw sensor data in Bayer format

			 into RGB (Red, Green, Blue) presentation. Then add

			 outputs of estimation of Y channel for following stream

			 processing by Firmware. The struct is defined as

			 :c:type:`ipu3_uapi_dm_config`.

			 struct ipu3_uapi_dm_config.

Color Correction	 Color Correction algo transforms sensor specific color

			 space to the standard "sRGB" color space. This is done

			 by applying 3x3 matrix defined in

			 :c:type:`ipu3_uapi_ccm_mat_config`.

Gamma correction	 Gamma correction :c:type:`ipu3_uapi_gamma_config` is a

			 struct ipu3_uapi_ccm_mat_config.

Gamma correction	 Gamma correction struct ipu3_uapi_gamma_config is a

			 basic non-linear tone mapping correction that is

			 applied per pixel for each pixel component.

CSC			 Color space conversion transforms each pixel from the

			 RGB primary presentation to YUV (Y: brightness,

			 UV: Luminance) presentation. This is done by applying

			 a 3x3 matrix defined in

			 :c:type:`ipu3_uapi_csc_mat_config`

			 struct ipu3_uapi_csc_mat_config

CDS			 Chroma down sampling

			 After the CSC is performed, the Chroma Down Sampling

			 is applied for a UV plane down sampling by a factor

			 of 2 in each direction for YUV 4:2:0 using a 4x2

			 configurable filter :c:type:`ipu3_uapi_cds_params`.

			 configurable filter struct ipu3_uapi_cds_params.

CHNR			 Chroma noise reduction

			 This block processes only the chrominance pixels and

			 performs noise reduction by cleaning the high

			 frequency noise.

			 See struct :c:type:`ipu3_uapi_yuvp1_chnr_config`.

			 See struct struct ipu3_uapi_yuvp1_chnr_config.

TCC			 Total color correction as defined in struct

			 :c:type:`ipu3_uapi_yuvp2_tcc_static_config`.

			 struct ipu3_uapi_yuvp2_tcc_static_config.

XNR3			 eXtreme Noise Reduction V3 is the third revision of

			 noise reduction algorithm used to improve image

			 quality. This removes the low frequency noise in the

			 captured image. Two related structs are  being defined,

			 :c:type:`ipu3_uapi_isp_xnr3_params` for ISP data memory

			 and :c:type:`ipu3_uapi_isp_xnr3_vmem_params` for vector

			 struct ipu3_uapi_isp_xnr3_params for ISP data memory

			 and struct ipu3_uapi_isp_xnr3_vmem_params for vector

			 memory.

TNR			 Temporal Noise Reduction block compares successive

			 frames in time to remove anomalies / noise in pixel

			 values. :c:type:`ipu3_uapi_isp_tnr3_vmem_params` and

			 :c:type:`ipu3_uapi_isp_tnr3_params` are defined for ISP

			 values. struct ipu3_uapi_isp_tnr3_vmem_params and

			 struct ipu3_uapi_isp_tnr3_params are defined for ISP

			 vector and data memory respectively.

======================== =======================================================
@@ -576,9 +576,9 @@ processor, while many others will use a set of fixed hardware blocks also 
called accelerator cluster (ACC) to crunch pixel data and produce statistics.



ACC parameters of individual algorithms, as defined by

:c:type:`ipu3_uapi_acc_param`, can be chosen to be applied by the user

space through struct :c:type:`ipu3_uapi_flags` embedded in

:c:type:`ipu3_uapi_params` structure. For parameters that are configured as

struct ipu3_uapi_acc_param, can be chosen to be applied by the user

space through struct struct ipu3_uapi_flags embedded in

struct ipu3_uapi_params structure. For parameters that are configured as

not enabled by the user space, the corresponding structs are ignored by the

driver, in which case the existing configuration of the algorithm will be

preserved.