图像插值算法¶

概述¶

在图像2D仿射变换一章里，我们介绍了resize中有若干个插值算法，本节，阿凯将讲解各种插值算法的实现过程。

keywords 2D仿射变换插值算法

何为插值?¶

一个图片从4×4 放大到8*8的时候，就会产生一些新的像素点（如下图红点所示），

如何给这些值赋值，就是interpolation 插值所要解决的问题。

插值方法一览¶

全部的插值方式请见文档 InterpolationFlags

这里我们只讲解五个插值方式。我们随机生成一个5×5的矩阵，然后用下面五种方式进行插值，效果如图所示：

201802182105

interpolation_algorithm_v1.py

import cv2
import numpy as np
from matplotlib import pyplot as plt


img = np.uint8(np.random.randint(0,255,size=(5,5)))
height,width= img.shape


# 声明新的维度
new_dimension = (25, 25)

plt.subplot(231)
plt.title("SRC Image")
plt.imshow(img,cmap='gray')

plt.subplot(232)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_NEAREST)
plt.title("INTER_NEAREST")
plt.imshow(resized,cmap='gray')


plt.subplot(233)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_LINEAR)
plt.title("INTER_LINEAR")
plt.imshow(resized,cmap='gray')


plt.subplot(234)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_AREA)
plt.title("INTER_AREA")
plt.imshow(resized,cmap='gray')


plt.subplot(235)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_CUBIC)
plt.title("INTER_CUBIC")
plt.imshow(resized,cmap='gray')


plt.subplot(236)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_LANCZOS4)
plt.title("INTER_LANCZOS4")
plt.imshow(resized,cmap='gray')

plt.show()

为了更加直观的观察，我们将cmap 换为seismic 分辨率从5*5 放大到1000*1000

interpolation_algorithm_v2.py

import cv2
import numpy as np
from matplotlib import pyplot as plt


img = np.uint8(np.random.randint(0,255,size=(5,5)))
height,width= img.shape


# 声明新的维度
new_dimension = (1000, 1000)

plt.subplot(231)
plt.title("SRC Image")
plt.imshow(img,cmap='seismic')

plt.subplot(232)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_NEAREST)
plt.title("INTER_NEAREST")
plt.imshow(resized,cmap='seismic')


plt.subplot(233)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_LINEAR)
plt.title("INTER_LINEAR")
plt.imshow(resized,cmap='seismic')


plt.subplot(234)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_AREA)
plt.title("INTER_AREA")
plt.imshow(resized,cmap='seismic')


plt.subplot(235)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_CUBIC)
plt.title("INTER_CUBIC")
plt.imshow(resized,cmap='seismic')


plt.subplot(236)
resized = cv2.resize(img, new_dimension, interpolation = cv2.INTER_LANCZOS4)
plt.title("INTER_LANCZOS4")
plt.imshow(resized,cmap='seismic')

plt.show()