media: ipu3: update meta format documentation

Language improvements, fix entity naming, make pipeline a graph and move
device usage documentation to device documentation ipu3.rst.

Signed-off-by: Yong Zhi <yong.zhi@intel.com>
Signed-off-by: Sakari Ailus <sakari.ailus@linux.intel.com>
Signed-off-by: Mauro Carvalho Chehab <mchehab+samsung@kernel.org>

Documentation/media/uapi/v4l/meta-formats.rst

@@ -19,8 +19,8 @@ These formats are used for the :ref:`metadata` interface only.
 .. toctree::
     :maxdepth: 1
 
-    pixfmt-meta-intel-ipu3
     pixfmt-meta-d4xx
+    pixfmt-meta-intel-ipu3
     pixfmt-meta-uvc
     pixfmt-meta-vsp1-hgo
     pixfmt-meta-vsp1-hgt

Documentation/media/uapi/v4l/pixfmt-meta-intel-ipu3.rst

@@ -30,21 +30,22 @@
 V4L2_META_FMT_IPU3_PARAMS ('ip3p'), V4L2_META_FMT_IPU3_3A ('ip3s')
 ******************************************************************
 
-.. c:type:: ipu3_uapi_stats_3a
+.. ipu3_uapi_stats_3a
 
 3A statistics
 =============
 
-For IPU3 ImgU, the 3A statistics accelerators collect different statistics over
+The IPU3 ImgU 3A statistics accelerators collect different statistics over
-an input bayer frame. Those statistics, defined in data struct :c:type:`ipu3_uapi_stats_3a`,
+an input Bayer frame. Those statistics are obtained from the "ipu3-imgu [01] 3a
-are obtained from "ipu3-imgu 3a stat" metadata capture video node, which are then
+stat" metadata capture video nodes, using the :c:type:`v4l2_meta_format`
-passed to user space for statistics analysis using :c:type:`v4l2_meta_format` interface.
+interface. They are formatted as described by the :c:type:`ipu3_uapi_stats_3a`
+structure.
 
 The statistics collected are AWB (Auto-white balance) RGBS (Red, Green, Blue and
 Saturation measure) cells, AWB filter response, AF (Auto-focus) filter response,
 and AE (Auto-exposure) histogram.
 
-struct :c:type:`ipu3_uapi_4a_config` saves configurable parameters for all above.
+The struct :c:type:`ipu3_uapi_4a_config` saves all configurable parameters.
 
 .. code-block:: c
 
@@ -60,105 +61,14 @@ struct :c:type:`ipu3_uapi_4a_config` saves configurable parameters for all above
 		struct ipu3_uapi_ff_status stats_3a_status;
 	};
 
-.. c:type:: ipu3_uapi_params
+.. ipu3_uapi_params
 
 Pipeline parameters
 ===================
 
-IPU3 pipeline has a number of image processing stages, each of which takes a
+The pipeline parameters are passed to the "ipu3-imgu [01] parameters" metadata
-set of parameters as input. The major stages of pipelines are shown here:
+output video nodes, using the :c:type:`v4l2_meta_format` interface. They are
-
+formatted as described by the :c:type:`ipu3_uapi_params` structure.
-Raw pixels -> Bayer Downscaling -> Optical Black Correction ->
-
-Linearization -> Lens Shading Correction -> White Balance / Exposure /
-
-Focus Apply -> Bayer Noise Reduction -> ANR -> Demosaicing -> Color
-
-Correction Matrix -> Gamma correction -> Color Space Conversion ->
-
-Chroma Down Scaling -> Chromatic Noise Reduction -> Total Color
-
-Correction -> XNR3 -> TNR -> DDR
-
-The table below presents a description of the above algorithms.
-
-======================== =======================================================
-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`.
-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`.
-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`.
-BNR			 Bayer noise reduction block removes image noise by
-			 applying a bilateral filter.
-			 See :c:type:`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`.
-Demosaicing		 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`. (TODO)
-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
-			 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`
-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`.
-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`.
-TCC			 Total color correction as defined in struct
-			 :c:type:`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
-			 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
-			 vector and data memory respectively.
-======================== =======================================================
-
-A few stages of the pipeline will be executed by firmware running on the ISP
-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
-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.
 
 Both 3A statistics and pipeline parameters described here are closely tied to
 the underlying camera sub-system (CSS) APIs. They are usually consumed and
@@ -166,13 +76,6 @@ produced by dedicated user space libraries that comprise the important tuning
 tools, thus freeing the developers from being bothered with the low level
 hardware and algorithm details.
 
-It should be noted that IPU3 DMA operations require the addresses of all data
-structures (that includes both input and output) to be aligned on 32 byte
-boundaries.
-
-The meta data :c:type:`ipu3_uapi_params` will be sent to "ipu3-imgu parameters"
-video node in ``V4L2_BUF_TYPE_META_CAPTURE`` format.
-
 .. code-block:: c
 
 	struct ipu3_uapi_params {

Documentation/media/v4l-drivers/ipu3.rst

@@ -357,6 +357,153 @@ https://chromium.googlesource.com/chromiumos/platform/arc-camera/+/master/
 
 The source can be located under hal/intel directory.
 
+Overview of IPU3 pipeline
+=========================
+
+IPU3 pipeline has a number of image processing stages, each of which takes a
+set of parameters as input. The major stages of pipelines are shown here:
+
+.. kernel-render:: DOT
+   :alt: IPU3 ImgU Pipeline
+   :caption: IPU3 ImgU Pipeline Diagram
+
+   digraph "IPU3 ImgU" {
+       node [shape=box]
+       splines="ortho"
+       rankdir="LR"
+
+       a [label="Raw pixels"]
+       b [label="Bayer Downscaling"]
+       c [label="Optical Black Correction"]
+       d [label="Linearization"]
+       e [label="Lens Shading Correction"]
+       f [label="White Balance / Exposure / Focus Apply"]
+       g [label="Bayer Noise Reduction"]
+       h [label="ANR"]
+       i [label="Demosaicing"]
+       j [label="Color Correction Matrix"]
+       k [label="Gamma correction"]
+       l [label="Color Space Conversion"]
+       m [label="Chroma Down Scaling"]
+       n [label="Chromatic Noise Reduction"]
+       o [label="Total Color Correction"]
+       p [label="XNR3"]
+       q [label="TNR"]
+       r [label="DDR"]
+
+       { rank=same; a -> b -> c -> d -> e -> f }
+       { rank=same; g -> h -> i -> j -> k -> l }
+       { rank=same; m -> n -> o -> p -> q -> r }
+
+       a -> g -> m [style=invis, weight=10]
+
+       f -> g
+       l -> m
+   }
+
+The table below presents a description of the above algorithms.
+
+======================== =======================================================
+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`.
+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`.
+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`.
+BNR			 Bayer noise reduction block removes image noise by
+			 applying a bilateral filter.
+			 See :c:type:`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`.
+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`.
+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
+			 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`
+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`.
+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`.
+TCC			 Total color correction as defined in struct
+			 :c:type:`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
+			 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
+			 vector and data memory respectively.
+======================== =======================================================
+
+Other often encountered acronyms not listed in above table:
+
+	ACC
+		Accelerator cluster
+	AWB_FR
+		Auto white balance filter response statistics
+	BDS
+		Bayer downscaler parameters
+	CCM
+		Color correction matrix coefficients
+	IEFd
+		Image enhancement filter directed
+	Obgrid
+		Optical black level compensation
+	OSYS
+		Output system configuration
+	ROI
+		Region of interest
+	YDS
+		Y down sampling
+	YTM
+		Y-tone mapping
+
+A few stages of the pipeline will be executed by firmware running on the ISP
+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
+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.
+
 References
 ==========