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-rw-r--r--Documentation/media/uapi/v4l/meta-formats.rst2
-rw-r--r--Documentation/media/uapi/v4l/pixfmt-meta-intel-ipu3.rst119
-rw-r--r--Documentation/media/v4l-drivers/ipu3.rst147
3 files changed, 159 insertions, 109 deletions
diff --git a/Documentation/media/uapi/v4l/meta-formats.rst b/Documentation/media/uapi/v4l/meta-formats.rst
index 5f956fa784b7..b10ca9ee3968 100644
--- a/Documentation/media/uapi/v4l/meta-formats.rst
+++ b/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
diff --git a/Documentation/media/uapi/v4l/pixfmt-meta-intel-ipu3.rst b/Documentation/media/uapi/v4l/pixfmt-meta-intel-ipu3.rst
index 659e58aa9c93..7fb54339f4a7 100644
--- a/Documentation/media/uapi/v4l/pixfmt-meta-intel-ipu3.rst
+++ b/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
-an input bayer frame. Those statistics, defined in data struct :c:type:`ipu3_uapi_stats_3a`,
-are obtained from "ipu3-imgu 3a stat" metadata capture video node, which are then
-passed to user space for statistics analysis using :c:type:`v4l2_meta_format` interface.
+The IPU3 ImgU 3A statistics accelerators collect different statistics over
+an input Bayer frame. Those statistics are obtained from the "ipu3-imgu [01] 3a
+stat" metadata capture video nodes, using the :c:type:`v4l2_meta_format`
+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
-set of parameters as input. The major stages of pipelines are shown here:
-
-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.
+The pipeline parameters are passed to the "ipu3-imgu [01] parameters" metadata
+output video nodes, using the :c:type:`v4l2_meta_format` interface. They are
+formatted as described by the :c:type:`ipu3_uapi_params` structure.
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 {
diff --git a/Documentation/media/v4l-drivers/ipu3.rst b/Documentation/media/v4l-drivers/ipu3.rst
index 804f37300623..c9f780404eee 100644
--- a/Documentation/media/v4l-drivers/ipu3.rst
+++ b/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
==========