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* Copyright (c) 2017, Alliance for Open Media. All rights reserved
* This source code is subject to the terms of the BSD 2 Clause License and
* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
* was not distributed with this source code in the LICENSE file, you can
* obtain it at If the Alliance for Open
* Media Patent License 1.0 was not distributed with this source code in the
* PATENTS file, you can obtain it at
#ifdef __cplusplus
extern "C" {
#endif // __cplusplus
#include <stdint.h>
#include "aom_dsp/grain_synthesis.h"
#include "aom_scale/yv12config.h"
/*!\brief Wrapper of data required to represent linear system of eqns and soln.
typedef struct {
double *A;
double *b;
double *x;
int n;
} aom_equation_system_t;
/*!\brief Representation of a piecewise linear curve
* Holds n points as (x, y) pairs, that store the curve.
typedef struct {
double (*points)[2];
int num_points;
} aom_noise_strength_lut_t;
/*!\brief Init the noise strength lut with the given number of points*/
int aom_noise_strength_lut_init(aom_noise_strength_lut_t *lut, int num_points);
/*!\brief Frees the noise strength lut. */
void aom_noise_strength_lut_free(aom_noise_strength_lut_t *lut);
/*!\brief Evaluate the lut at the point x.
* \param[in] lut The lut data.
* \param[in] x The coordinate to evaluate the lut.
double aom_noise_strength_lut_eval(const aom_noise_strength_lut_t *lut,
double x);
/*!\brief Helper struct to model noise strength as a function of intensity.
* Internally, this structure holds a representation of a linear system
* of equations that models noise strength (standard deviation) as a
* function of intensity. The mapping is initially stored using a
* piecewise representation with evenly spaced bins that cover the entire
* domain from [min_intensity, max_intensity]. Each observation (x,y) gives a
* constraint of the form:
* y_{i} (1 - a) + y_{i+1} a = y
* where y_{i} is the value of bin i and x_{i} <= x <= x_{i+1} and
* a = x/(x_{i+1} - x{i}). The equation system holds the corresponding
* normal equations.
* As there may be missing data, the solution is regularized to get a
* complete set of values for the bins. A reduced representation after
* solving can be obtained by getting the corresponding noise_strength_lut_t.
typedef struct {
aom_equation_system_t eqns;
double min_intensity;
double max_intensity;
int num_bins;
int num_equations;
double total;
} aom_noise_strength_solver_t;
/*!\brief Initializes the noise solver with the given number of bins.
* Returns 0 if initialization fails.
* \param[in] solver The noise solver to be initialized.
* \param[in] num_bins Number of bins to use in the internal representation.
* \param[in] bit_depth The bit depth used to derive {min,max}_intensity.
int aom_noise_strength_solver_init(aom_noise_strength_solver_t *solver,
int num_bins, int bit_depth);
void aom_noise_strength_solver_free(aom_noise_strength_solver_t *solver);
/*!\brief Gets the x coordinate of bin i.
* \param[in] i The bin whose coordinate to query.
double aom_noise_strength_solver_get_center(
const aom_noise_strength_solver_t *solver, int i);
/*!\brief Add an observation of the block mean intensity to its noise strength.
* \param[in] block_mean The average block intensity,
* \param[in] noise_std The observed noise strength.
void aom_noise_strength_solver_add_measurement(
aom_noise_strength_solver_t *solver, double block_mean, double noise_std);
/*!\brief Solves the current set of equations for the noise strength. */
int aom_noise_strength_solver_solve(aom_noise_strength_solver_t *solver);
/*!\brief Fits a reduced piecewise linear lut to the internal solution
* \param[in] max_num_points The maximum number of output points
* \param[out] lut The output piecewise linear lut.
int aom_noise_strength_solver_fit_piecewise(
const aom_noise_strength_solver_t *solver, int max_num_points,
aom_noise_strength_lut_t *lut);
/*!\brief Helper for holding precomputed data for finding flat blocks.
* Internally a block is modeled with a low-order polynomial model. A
* planar model would be a bunch of equations like:
* <[y_i x_i 1], [a_1, a_2, a_3]> = b_i
* for each point in the block. The system matrix A with row i as [y_i x_i 1]
* is maintained as is the inverse, inv(A'*A), so that the plane parameters
* can be fit for each block.
typedef struct {
double *AtA_inv;
double *A;
int num_params; // The number of parameters used for internal low-order model
int block_size; // The block size the finder was initialized with
double normalization; // Normalization factor (1 / (2^(bit_depth) - 1))
int use_highbd; // Whether input data should be interpreted as uint16
} aom_flat_block_finder_t;
/*!\brief Init the block_finder with the given block size, bit_depth */
int aom_flat_block_finder_init(aom_flat_block_finder_t *block_finder,
int block_size, int bit_depth, int use_highbd);
void aom_flat_block_finder_free(aom_flat_block_finder_t *block_finder);
/*!\brief Helper to extract a block and low order "planar" model. */
void aom_flat_block_finder_extract_block(
const aom_flat_block_finder_t *block_finder, const uint8_t *const data,
int w, int h, int stride, int offsx, int offsy, double *plane,
double *block);
/*!\brief Runs the flat block finder on the input data.
* Find flat blocks in the input image data. Returns a map of
* flat_blocks, where the value of flat_blocks map will be non-zero
* when a block is determined to be flat. A higher value indicates a bigger
* confidence in the decision.
int aom_flat_block_finder_run(const aom_flat_block_finder_t *block_finder,
const uint8_t *const data, int w, int h,
int stride, uint8_t *flat_blocks);
// The noise shape indicates the allowed coefficients in the AR model.
enum {
} UENUM1BYTE(aom_noise_shape);
// The parameters of the noise model include the shape type, lag, the
// bit depth of the input images provided, and whether the input images
// will be using uint16 (or uint8) representation.
typedef struct {
aom_noise_shape shape;
int lag;
int bit_depth;
int use_highbd;
} aom_noise_model_params_t;
/*!\brief State of a noise model estimate for a single channel.
* This contains a system of equations that can be used to solve
* for the auto-regressive coefficients as well as a noise strength
* solver that can be used to model noise strength as a function of
* intensity.
typedef struct {
aom_equation_system_t eqns;
aom_noise_strength_solver_t strength_solver;
int num_observations; // The number of observations in the eqn system
double ar_gain; // The gain of the current AR filter
} aom_noise_state_t;
/*!\brief Complete model of noise for a planar video
* This includes a noise model for the latest frame and an aggregated
* estimate over all previous frames that had similar parameters.
typedef struct {
aom_noise_model_params_t params;
aom_noise_state_t combined_state[3]; // Combined state per channel
aom_noise_state_t latest_state[3]; // Latest state per channel
int (*coords)[2]; // Offsets (x,y) of the coefficient samples
int n; // Number of parameters (size of coords)
int bit_depth;
} aom_noise_model_t;
/*!\brief Result of a noise model update. */
enum {
} UENUM1BYTE(aom_noise_status_t);
/*!\brief Initializes a noise model with the given parameters.
* Returns 0 on failure.
int aom_noise_model_init(aom_noise_model_t *model,
const aom_noise_model_params_t params);
void aom_noise_model_free(aom_noise_model_t *model);
/*!\brief Updates the noise model with a new frame observation.
* Updates the noise model with measurements from the given input frame and a
* denoised variant of it. Noise is sampled from flat blocks using the flat
* block map.
* Returns a noise_status indicating if the update was successful. If the
* Update was successful, the combined_state is updated with measurements from
* the provided frame. If status is OK or DIFFERENT_NOISE_TYPE, the latest noise
* state will be updated with measurements from the provided frame.
* \param[in,out] noise_model The noise model to be updated
* \param[in] data Raw frame data
* \param[in] denoised Denoised frame data.
* \param[in] w Frame width
* \param[in] h Frame height
* \param[in] strides Stride of the planes
* \param[in] chroma_sub_log2 Chroma subsampling for planes != 0.
* \param[in] flat_blocks A map to blocks that have been determined flat
* \param[in] block_size The size of blocks.
aom_noise_status_t aom_noise_model_update(
aom_noise_model_t *const noise_model, const uint8_t *const data[3],
const uint8_t *const denoised[3], int w, int h, int strides[3],
int chroma_sub_log2[2], const uint8_t *const flat_blocks, int block_size);
/*\brief Save the "latest" estimate into the "combined" estimate.
* This is meant to be called when the noise modeling detected a change
* in parameters (or for example, if a user wanted to reset estimation at
* a shot boundary).
void aom_noise_model_save_latest(aom_noise_model_t *noise_model);
/*!\brief Converts the noise_model parameters to the corresponding
* grain_parameters.
* The noise structs in this file are suitable for estimation (e.g., using
* floats), but the grain parameters in the bitstream are quantized. This
* function does the conversion by selecting the correct quantization levels.
int aom_noise_model_get_grain_parameters(aom_noise_model_t *const noise_model,
aom_film_grain_t *film_grain);
/*!\brief Perform a Wiener filter denoising in 2D using the provided noise psd.
* \param[in] data Raw frame data
* \param[out] denoised Denoised frame data
* \param[in] w Frame width
* \param[in] h Frame height
* \param[in] stride Stride of the planes
* \param[in] chroma_sub_log2 Chroma subsampling for planes != 0.
* \param[in] noise_psd The power spectral density of the noise
* \param[in] block_size The size of blocks
* \param[in] bit_depth Bit depth of the image
* \param[in] use_highbd If true, uint8 pointers are interpreted as
* uint16 and stride is measured in uint16.
* This must be true when bit_depth >= 10.
int aom_wiener_denoise_2d(const uint8_t *const data[3], uint8_t *denoised[3],
int w, int h, int stride[3], int chroma_sub_log2[2],
float *noise_psd[3], int block_size, int bit_depth,
int use_highbd);
struct aom_denoise_and_model_t;
/*!\brief Denoise the buffer and model the residual noise.
* This is meant to be called sequentially on input frames. The input buffer
* is denoised and the residual noise is modelled. The current noise estimate
* is populated in film_grain. Returns true on success. The grain.apply_grain
* parameter will be true when the input buffer was successfully denoised and
* grain was modelled. Returns false on error.
* \param[in] ctx Struct allocated with aom_denoise_and_model_alloc
* that holds some buffers for denoising and the current
* noise estimate.
* \param[in/out] buf The raw input buffer to be denoised.
* \param[out] grain Output film grain parameters
int aom_denoise_and_model_run(struct aom_denoise_and_model_t *ctx,
YV12_BUFFER_CONFIG *buf, aom_film_grain_t *grain);
/*!\brief Allocates a context that can be used for denoising and noise modeling.
* \param[in] bit_depth Bit depth of buffers this will be run on.
* \param[in] block_size Block size for noise modeling and flat block
* estimation
* \param[in] noise_level The noise_level (2.5 for moderate noise, and 5 for
* higher levels of noise)
struct aom_denoise_and_model_t *aom_denoise_and_model_alloc(int bit_depth,
int block_size,
float noise_level);
/*!\brief Frees the denoise context allocated with aom_denoise_and_model_alloc
void aom_denoise_and_model_free(struct aom_denoise_and_model_t *denoise_model);
#ifdef __cplusplus
} // extern "C"
#endif // __cplusplus