使用最邻近插值将图像放大1.5倍吧!
Opencv最近邻插值在图像放大时补充的像素取最临近的像素的值。由于方法简单,所以处理速度很快,但是放大图像画质劣化明显。
使用下面的公式放大图像吧!I’为放大后图像,I为放大前图像,a为放大率,方括号是四舍五入取整操作:
I'(x,y) = I([\frac{x}{a}], [\frac{y}{a}])
python实现:
import cv2
import numpy as np
import matplotlib.pyplot as plt
# Nereset Neighbor interpolation
def nn_interpolate(img, ax=1, ay=1):
H, W, C = img.shape
aH = int(ay * H)
aW = int(ax * W)
y = np.arange(aH).repeat(aW).reshape(aW, -1)
x = np.tile(np.arange(aW), (aH, 1))
y = np.round(y / ay).astype(np.int)
x = np.round(x / ax).astype(np.int)
out = img[y,x]
out = out.astype(np.uint8)
return out
# Read image
img = cv2.imread("imori.jpg").astype(np.float)
# Nearest Neighbor
out = nn_interpolate(img, ax=1.5, ay=1.5)
# Save result
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.imwrite("out.jpg", out)
c++实现:
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <math.h>
// nearest nieghbor
cv::Mat nearest_neighbor(cv::Mat img, double rx, double ry){
// get height and width
int width = img.cols;
int height = img.rows;
int channel = img.channels();
// get resized shape
int resized_width = (int)(width * rx);
int resized_height = (int)(height * ry);
int x_before, y_before;
// output image
cv::Mat out = cv::Mat::zeros(resized_height, resized_width, CV_8UC3);
// nearest neighbor interpolation
for (int y = 0; y < resized_height; y++){
y_before = (int)round(y / ry);
y_before = fmin(y_before, height - 1);
for (int x = 0; x < resized_width; x++){
x_before = (int)round(x / rx);
x_before = fmin(x_before, width - 1);
// assign pixel to new position
for (int c = 0; c < channel; c++){
out.at<cv::Vec3b>(y, x)[c] = img.at<cv::Vec3b>(y_before, x_before)[c];
}
}
}
return out;
}
int main(int argc, const char* argv[]){
// read image
cv::Mat img = cv::imread("imori.jpg", cv::IMREAD_COLOR);
// nearest neighbor
cv::Mat out = nearest_neighbor(img, 1.5, 1.5);
//cv::imwrite("out.jpg", out);
cv::imshow("answer", out);
cv::waitKey(0);
cv::destroyAllWindows();
return 0;
}
输入:
输出: