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插值

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Bilinear interpolation would be order=1, nearest is order=0, and cubic is the default (order=3).

舉例說明

import numpy as np import scipy.ndimagex = np.arange(64).reshape(8,8)print 'Original array:' print xprint 'Resampled by a factor of 2 with nearest interpolation:' print scipy.ndimage.zoom(x, 2, order=0)print 'Resampled by a factor of 2 with bilinear interpolation:' print scipy.ndimage.zoom(x, 2, order=1)print 'Resampled by a factor of 2 with cubic interpolation:' print scipy.ndimage.zoom(x, 2, order=3)print 'Downsampled by a factor of 0.5 with default interpolation:' print(scipy.ndimage.zoom(x, 0.5))

結果

Original array: array([[ 0, 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]]) Resampled by a factor of 2 with nearest interpolation: [[ 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7][ 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7][ 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15][ 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15][16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23][16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23][24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31][24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31][32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39][32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39][40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47][40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47][48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55][48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55][56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63][56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63]]Resampled by a factor of 2 with bilinear interpolation: [[ 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7][ 4 4 5 5 6 6 7 7 7 8 8 9 9 10 10 11][ 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 14][11 12 12 13 13 14 14 14 15 15 16 16 17 17 18 18][15 15 16 16 17 17 18 18 19 19 20 20 21 21 21 22][19 19 20 20 21 21 21 22 22 23 23 24 24 25 25 26][22 23 23 24 24 25 25 26 26 27 27 28 28 28 29 29][26 27 27 28 28 28 29 29 30 30 31 31 32 32 33 33][30 30 31 31 32 32 33 33 34 34 35 35 35 36 36 37][34 34 35 35 35 36 36 37 37 38 38 39 39 40 40 41][37 38 38 39 39 40 40 41 41 42 42 42 43 43 44 44][41 42 42 42 43 43 44 44 45 45 46 46 47 47 48 48][45 45 46 46 47 47 48 48 49 49 49 50 50 51 51 52][49 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56][52 53 53 54 54 55 55 56 56 56 57 57 58 58 59 59][56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63]]Resampled by a factor of 2 with cubic interpolation: [[ 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7][ 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 9][ 7 8 8 9 9 10 10 11 11 12 12 12 13 13 14 14][12 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19][15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22][19 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26][22 23 23 24 24 25 25 26 26 27 27 27 28 28 29 29][26 26 27 28 28 28 29 29 30 30 31 31 32 32 33 33][30 30 31 31 32 32 33 33 34 34 35 35 35 36 37 37][34 34 35 35 36 36 36 37 37 38 38 39 39 40 40 41][37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 44][41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48][44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 51][49 49 50 50 51 51 51 52 52 53 53 54 54 55 55 56][54 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61][56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63]]Downsampled by a factor of 0.5 with default interpolation: [[ 0 2 5 7][19 21 23 26][37 40 42 44][56 58 61 63]]

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參考文獻

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Resampling a numpy array representing an image

機器學習入門必備的13張小抄

總結

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