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author | Yong Zhi <yong.zhi@intel.com> | 2019-01-24 19:05:31 -0500 |
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committer | Mauro Carvalho Chehab <mchehab+samsung@kernel.org> | 2019-02-18 15:16:58 -0500 |
commit | b8726aea59de780a2eb95897f133284d742d6c83 (patch) | |
tree | a959e56fa352439ac3775eb432914282d88fe030 /Documentation/media | |
parent | 27e2add8ae8fcae07e2e8d3ea5b3699572290ef3 (diff) | |
download | linux-b8726aea59de780a2eb95897f133284d742d6c83.tar.gz linux-b8726aea59de780a2eb95897f133284d742d6c83.tar.bz2 linux-b8726aea59de780a2eb95897f133284d742d6c83.zip |
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>
Diffstat (limited to 'Documentation/media')
-rw-r--r-- | Documentation/media/uapi/v4l/meta-formats.rst | 2 | ||||
-rw-r--r-- | Documentation/media/uapi/v4l/pixfmt-meta-intel-ipu3.rst | 119 | ||||
-rw-r--r-- | Documentation/media/v4l-drivers/ipu3.rst | 147 |
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 ========== |