Newer
Older
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
/* The copyright in this software is being made available under the BSD
* License, included below. This software may be subject to other third party
* and contributor rights, including patent rights, and no such rights are
* granted under this license.
*
* Copyright (c) 2010-2019, ITU/ISO/IEC
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* * Neither the name of the ITU/ISO/IEC nor the names of its contributors may
* be used to endorse or promote products derived from this software without
* specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS
* BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
* THE POSSIBILITY OF SUCH DAMAGE.
*/
/** \file MatrixIntraPrediction.h
\brief matrix-based intra prediction class (header)
*/
#ifndef __MATRIXINTRAPPREDICTION__
#define __MATRIXINTRAPPREDICTION__
#include "Unit.h"
static const int MIP_MAX_INPUT_SIZE = 8;
static const int MIP_MAX_REDUCED_OUTPUT_SAMPLES = 64;
namespace Mip
{
class PredictorMIP
{
public:
PredictorMIP();
void deriveBoundaryData(const CPelBuf& src, const Area& block, const int bitDepth, const AvailableInfo &availInfo);
void getPrediction (int* const result, const int modeIdx, const int bitDepth);
private:
static_vector<int, MIP_MAX_INPUT_SIZE> m_reducedBoundary; // downsampled boundary of a block
static_vector<int, MIP_MAX_INPUT_SIZE> m_reducedBoundaryTransposed; // downsampled, transposed boundary of a block
static_vector<int, MIP_MAX_WIDTH> m_boundaryForUpsamplingTop; // top boundary samples for upsampling
static_vector<int, MIP_MAX_HEIGHT> m_boundaryForUpsamplingLeft; // left boundary samples for upsampling
Size m_blockSize;
int m_numModes;
Size m_reducedBoundarySize;
Size m_reducedPredictionSize;
Size m_boundarySizeForUpsampling;
unsigned int m_upsmpFactorHor;
unsigned int m_upsmpFactorVer;
void initPredBlockParams(const Size& block);
static void boundaryDownsampling1D( int* reducedDst, int* fullSrcAndIntermediateDst, const SizeType srcLen, const SizeType dstLen, const bool saveIntermediate, const SizeType intermediateLen );
static void doDownsampling( int* dst, const int* src, const SizeType srcLen, const SizeType dstLen );
void predictionUpsampling( int* const dst, const int* const src, const bool transpose ) const;
static void predictionUpsampling1D( int* const dst, const int* const src, const int* const bndry,
const SizeType srcSizeUpsmpDim, const SizeType srcSizeOrthDim,
const SizeType srcStep, const SizeType srcStride,
const SizeType dstStep, const SizeType dstStride,
const unsigned int upsmpFactor );
void getMatrixBias( const short*& matrix, const short*& bias, const int modeIdx ) const;
void getShifts( int &shiftMatrix, int &shiftBias, const int modeIdx, const int bitDepth ) const;
bool isTransposed( const int modeIdx ) const;
int getWeightIdx( const int modeIdx ) const;
void xComputeMatrixTimesRedBndryPlusBias( int*const result, const int* const input,
const short*matrix, const short*bias,
const bool leaveHorOut, const bool leaveVerOut,
Philipp Merkle
committed
const int shiftMatrix, const int shiftBias,
const bool transpose, const bool needUpsampling );
};
}
class MatrixIntraPrediction
{
public:
MatrixIntraPrediction();
Mip::PredictorMIP m_predictorMip;
void prepareInputForPred(const CPelBuf &src, const Area& puArea, const int bitDepth, const AvailableInfo &availInfo);
void predBlock( const Size &puSize, const int modeIdx, PelBuf &dst, const int bitDepth );
};
#endif //__MATRIXINTRAPPREDICTION__