1. 最常见四种插值算法
   INTER_NEAREST = 0 # 最近邻插值
   INTER_LINEAR = 1 # 双线性插值
   INTER_CUBIC = 2 # 双立方插值，不仅考虑周围像素点，还具有反锯齿功能
   INTER_LANCZOS4 = 4 # 卢卡斯插值，本质是基于能量场的插值算法
2. 相关的应用场景：
   几何变换、透视变换中插值计算新像素；
   resize：如果size不为零，使用size做放缩插值，否则根据fx与fy放缩。

C++

#include<opencv2/opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main(int argc, char** argv) {
    Mat src = imread("D:/vcprojects/images/test.png");
    if (src.empty()) {
        printf("could not load image...\n");
        return -1;
    }
    imshow("input", src);

    int h = src.rows;
    int w = src.cols;
    float fx = 0.0, fy = 0.0;
    Mat dst = Mat::zeros(src.size(), src.type());
    resize(src, dst, Size(w * 2, h * 2), fx = 0, fy = 0, INTER_NEAREST);
    imshow("INTER_NEAREST", dst);

    resize(src, dst, Size(w * 2, h * 2), fx = 0, fy = 0, INTER_LINEAR);
    imshow("INTER_LINEAR", dst);

    resize(src, dst, Size(w * 2, h * 2), fx = 0, fy = 0, INTER_CUBIC);
    imshow("INTER_CUBIC", dst);

    resize(src, dst, Size(w * 2, h * 2), fx = 0, fy = 0, INTER_LANCZOS4);
    imshow("INTER_LANCZOS4", dst);

    waitKey(0);
    return 0;
}

Python

import cv2 as cv

src = cv.imread("D:/vcprojects/images/test.png")
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("input", src)

h, w = src.shape[:2]
print(h, w)
dst = cv.resize(src, (w*2, h*2), fx=0.75, fy=0.75, interpolation=cv.INTER_NEAREST) # size和fxfy都设置，则size生效。若size为（0,0）则fxfy生效。
cv.imshow("INTER_NEAREST", dst)

dst = cv.resize(src, (w*2, h*2), interpolation=cv.INTER_LINEAR)
cv.imshow("INTER_LINEAR", dst)

dst = cv.resize(src, (w*2, h*2), interpolation=cv.INTER_CUBIC)
cv.imshow("INTER_CUBIC", dst)

dst = cv.resize(src, (w*2, h*2), interpolation=cv.INTER_LANCZOS4)
cv.imshow("INTER_LANCZOS4", dst)

cv.warpAffine()

cv.waitKey(0)
cv.destroyAllWindows()