Exemplo n.º 1
0
        public List<Vector<double>> AddNoise(List<Vector<double>> points,
            double variance, int seed = 0)
        {
            List<Vector<double>> noisedPoints = new List<Vector<double>>(points.Count);
            int pointSize = points[0].Count;

            GaussianNoiseGenerator noise = new GaussianNoiseGenerator();
            noise.Variance = variance;
            noise.Mean = 0.0;
            noise.RandomSeed = seed != 0;
            noise.Seed = seed;
            noise.UpdateDistribution();

            for(int i = 0; i < _pointsCount; ++i)
            {
                Vector<double> cpoint = new DenseVector(pointSize);
                for(int p = 0; p < pointSize - 1; ++p)
                {
                    cpoint[p] = points[i][p] + noise.GetSample();
                }
                cpoint[pointSize - 1] = 1.0f;

                noisedPoints.Add(cpoint);
            }

            return noisedPoints;
        }
Exemplo n.º 2
0
        public List<CalibrationPoint> AddNoise(List<CalibrationPoint> points,
            double varReal, double varImg, int seed = 0)
        {
            List<CalibrationPoint> noisedPoints = new List<CalibrationPoint>(points.Count);

            GaussianNoiseGenerator noiseReal = new GaussianNoiseGenerator();
            noiseReal.Variance = varReal;
            noiseReal.Mean = 0.0;
            noiseReal.RandomSeed = seed != 0;
            noiseReal.Seed = seed;
            noiseReal.UpdateDistribution();

            GaussianNoiseGenerator noiseImage = new GaussianNoiseGenerator();
            noiseImage.Variance = varImg;
            noiseImage.Mean = 0.0;
            noiseImage.RandomSeed = seed != 0;
            noiseImage.Seed = seed;
            noiseImage.UpdateDistribution();

            for(int i = 0; i < _pointsCount; ++i)
            {
                CalibrationPoint cpoint = new CalibrationPoint();

                cpoint.RealX = points[i].RealX + noiseReal.GetSample();
                cpoint.RealY = points[i].RealY + noiseReal.GetSample();
                cpoint.RealZ = points[i].RealZ + noiseReal.GetSample();

                cpoint.ImgX = points[i].ImgX + noiseImage.GetSample();
                cpoint.ImgY = points[i].ImgY + noiseImage.GetSample();

                noisedPoints.Add(cpoint);
            }

            return noisedPoints;
        }
Exemplo n.º 3
0
        public Matrix<double> AddNoise(Matrix<double> matrix)
        {
            Matrix<double> noisedMat = matrix.Clone();

            GaussianNoiseGenerator noise = new GaussianNoiseGenerator();
            noise.Mean = 0.0;
            noise.RandomSeed = false;
            Random rand = new Random(_seed);

            for(int r = 0; r < noisedMat.RowCount; ++r)
            {
                for(int c = 0; c < noisedMat.ColumnCount; ++c)
                {
                    noise.Seed = rand.Next();
                    noise.Variance = Math.Abs(noisedMat[r, c]) < 1e-12 ?
                        1e-12 : Math.Abs(noisedMat[r, c]) / 100.0;
                    noise.UpdateDistribution();

                    noisedMat[r, c] = noisedMat[r, c] + noise.GetSample();
                }
            }

            return noisedMat;
        }