opencv實現對圖像的插值操作 最近鄰、雙線性、雙三次

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python 為例

一. 函數原型

        dst=cv.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]])

        參數含義：

        src：input image.

        dst：output image; it has the size dsize (when it is non-zero) or the size computed from src.size(), fx, and fy; the type of dst is the same as of src.

        dsize：output image size; if it equals zero, it is computed as:

                dsize = Size(round(fx*src.cols), round(fy*src.rows))

                Either dsize or both fx and fy must be non-zero.

        fx ：scale factor along the horizontal axis; when it equals 0, it is computed as

(double)dsize.width/src.cols

        fy ：scale factor along the vertical axis; when it equals 0, it is computed as

(double)dsize.height/src.rows

        interpolation：interpolation method, see InterpolationFlags

三種插值方法的 interpolation 參數

 

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二. 實驗代碼：

import cv2
import numpy as np 

# 讀入灰度圖像
im_path='../paojie_g.jpg'
img = cv2.imread(im_path,0)
# 注意應該先寫寬度img.shape[1]*2,再寫高度img.shape[0]*2
NN_interpolation = cv2.resize(img,(img.shape[1]*2,img.shape[0]*2),interpolation=cv2.INTER_NEAREST)
BiLinear_interpolation =  cv2.resize(img,(img.shape[1]*2,img.shape[0]*2),interpolation=cv2.INTER_LINEAR)
BiCubic_interpolation = cv2.resize(img,(img.shape[1]*2,img.shape[0]*2),interpolation=cv2.INTER_CUBIC)

cv2.imshow('NN_interpolation',NN_interpolation)
cv2.imwrite('NN_interpolation.jpg',NN_interpolation)
cv2.imshow('BiLinear_interpolation',BiLinear_interpolation)
cv2.imwrite('BiLinear_interpolation.jpg',BiLinear_interpolation)
cv2.imshow('BiCubic_interpolation',BiCubic_interpolation)
cv2.imwrite('BiCubic_interpolation.jpg',BiCubic_interpolation)
cv2.waitKey(0)
cv2.destroyAllWindows()

 

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三. 實驗結果：

原圖 ↑

 

NN_interpolation x2 ↑

 

BiLinear_interpolation  x2 ↑

 

BiCubic_interpolation   x2 ↑

 

        可以看到，最近鄰插值算法放大圖像后，目標圖像邊緣出現了明顯的鋸齒；而雙線性和雙三次插值算法沒有出現明顯的鋸齒邊緣。

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四. 參考內容：

　　https://www.jianshu.com/p/f360462f0db4