/* * 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 www.aomedia.org/license/software. 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 www.aomedia.org/license/patent. */ #ifndef AOM_AOM_DSP_NOISE_MODEL_H_ #define AOM_AOM_DSP_NOISE_MODEL_H_ #ifdef __cplusplus extern "C" { #endif // __cplusplus #include #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. typedef enum { AOM_NOISE_SHAPE_DIAMOND = 0, AOM_NOISE_SHAPE_SQUARE = 1 } 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. */ typedef enum { AOM_NOISE_STATUS_OK = 0, AOM_NOISE_STATUS_INVALID_ARGUMENT, AOM_NOISE_STATUS_INSUFFICIENT_FLAT_BLOCKS, AOM_NOISE_STATUS_DIFFERENT_NOISE_TYPE, AOM_NOISE_STATUS_INTERNAL_ERROR, } 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 #endif // AOM_AOM_DSP_NOISE_MODEL_H_