如何在不改变像素值的情况下对图像数组进行采样

Question

我有图像分割项目，并且以像素值代表标签的图像形式给出了地面实况标签。我需要调整图像和标签的大小，同时将标签保持在相同的值集中。

我尝试了很多东西，都改变了设置的值。

让我们创建虚拟数据

from skimage.transform import rescale, resize
from scipy import ndimage
from PIL import Image
import cv2

mask = np.zeros((30,20), dtype=np.uint16)
mask[22:26,12:30]=70
mask[25:27,14:17]=30
print('original label', mask.shape, np.unique(mask))

输出：原始标签形状：(30, 20) 原始标签值：[0 30 70]

我需要调整标签大小，所以结果将只有 0、30、70 个值。

我试过的

skimage_resized = resize(mask, (mask.shape[0]//2, mask.shape[1]//2), mode='constant')
print(skimage_resized.shape, np.unique(mask_resized))

skimage_rescale = rescale(mask, 1.0/2.0, mode='constant')
print(skimage_rescale.shape, np.unique(mask_resized))

ndimage_resized = ndimage.interpolation.zoom(mask, 0.5)
print(ndimage_resized.shape, np.unique(mask_resized))


cv2_resized = cv2.resize(mask, (mask.shape[0]//2, mask.shape[1]//2),
                        interpolation=cv2.INTER_NEAREST)
print(cv2_resized.shape, np.unique(mask_resized))

mask_pil = Image.fromarray(mask, mode=None)
pil_resized = mask_pil.thumbnail((mask.shape[0]//2, mask.shape[1]//2), Image.NEAREST)
print(skimage_resized.shape, np.unique(pil_resized))

输出：

(15, 10) [ 0  5  6 28 29 30 31 61 62 65 70 71 74 75 76]
(15, 10) [ 0  5  6 28 29 30 31 61 62 65 70 71 74 75 76]
(15, 10) [ 0  5  6 28 29 30 31 61 62 65 70 71 74 75 76]
(10, 15) [ 0  5  6 28 29 30 31 61 62 65 70 71 74 75 76]
(15, 10) [None]

Answer 1

来自 docs（强调我的）：

Note that when down-sampling an image, resize and rescale should perform Gaussian smoothing to avoid aliasing artifacts. See the anti_aliasing and anti_aliasing_sigma arguments to these functions.

Downscale serves the purpose of down-sampling an n-dimensional image by integer factors using the local mean on the elements of each block of the size factors given as a parameter to the function.

您的问题的一种可能解决方法是通过 basic slicing:

进行下采样

import numpy as np

dx, dy = 2, 2
mask = np.zeros((30, 20), dtype=np.uint16)
mask[22:26, 12:30] = 70
mask[25:27, 14:17] = 30

downsampled = mask[::dx, ::dy]
print(downsampled.shape, np.unique(downsampled))

上面代码片段的输出是：

(15, 10) [ 0 30 70]

Answer 2

使用 openCV 找到解决方案。

import numpy as np
import cv2
resizeto = 2
small_lable = cv2.resize(mask, (mask.shape[1]//resizeto, 
                         mask.shape[0]//resizeto),
                        interpolation=cv2.INTER_NEAREST)
small_lable = (np.array(small_lable)).astype('uint8')
print(small_lable.shape, np.unique(small_lable))
plt.imshow(small_lable)

输出：

(15, 10) [ 0 30 70]

如何在不改变像素值的情况下对图像数组进行采样

How to down sample image array, without changing pixel values

image

python-imaging-library

scikit-image

ndimage

cv2

我尝试了很多东西，都改变了设置的值。