使用Python进行图像缩放的最近邻插值

问题描述

• 我正在尝试实现最近邻居插值技术，以在Python中缩放图像。

• 当比例因子小于2 时，我的代码似乎可以运行。

• 否则，我得到以下错误： ...\NN_Zoom\NN.py",line 50,in NN_interpolation zoom[i][j] = im[near_neighbour(X,P)[0]][near_neighbour(X,P)[1]] IndexError: index 600 is out of bounds for axis 0 with size 600

例如：缩放形状为：（1500，1500）图像形状为：（600，600）

#==================================
# Import Libraries
#==================================
import numpy as np
import matplotlib.pyplot as plt 
from skimage.io import imread

#----------------------------------
# Euclidian distance
#==================================
def euclidian_dist(a,b):
    '''
    Euclidian distance between 2 points a(x_a,y_a) and b(x_b,y_b)
    distance = Square Root ( (x_a - x_b)^2 +  (y_a - y_b)^2 )
    '''
    return np.sqrt(((a[0]-b[0])**2)+((a[1]-b[1])**2))

#----------------------------------
# Nearest Neighbour
#==================================
def near_neighbour(X,P):
    '''
    The nearest neighbour of point X(x,y) to the centroid P(x_p,y_p)
    The Neighbourhood is defined by the Upper-Left corner of the point X,which means 3 neighbours and the point X. 
    '''
    i,j = X[0],X[1]
    A = [[i,j],[i,j+1],[i+1,j+1]]
    dist = [euclidian_dist(A[0],P),euclidian_dist(A[1],euclidian_dist(A[2],euclidian_dist(A[3],P)]
    minpos = dist.index(min(dist))
    return A[minpos]        

#----------------------------------
# Nearest Neighbour Interpolation
#==================================
def NN_interpolation(im,scale_factor):
    '''
    Interpolation of the image im with scale factor scale_factor,using Nearest Neighbour.
    '''
    row,col = im.shape[0],im.shape[1]
    n_row,n_col = int(scale_factor * row),int(scale_factor * col)
    # fill in  img
    zoom = np.arange(n_row*n_col).reshape(n_row,n_col)
    print("zoom shape is: ",zoom.shape,"image shape is: ",im.shape,'\n')
    for i in range(n_row):
        for j in range(n_col):
            P = [float(i)/scale_factor,float(j)/scale_factor]
            X = [int(i) for i in P]
            zoom[i][j] = im[near_neighbour(X,P)[1]]
    return zoom
#-------------------------
# Example
#=========================
im = imread('image.png')[...,0]

J = NN_interpolation(im,1.5)

plt.figure(num='NN-Interpolation')
plt.subplot(121)
imgplot = plt.imshow(im,cmap="gray") # displaying the image
plt.title('Original')

plt.subplot(122)
imgplot = plt.imshow(J,cmap="gray") # displaying the image
plt.title('Zoomed')

plt.show()

print(im.shape,J.shape)

解决方法

• 您的问题是由缩放尺寸除以比例因子时的向上舍入引起的。

• 解决方案是使用 floor 功能：

# P = [float(i)/scale_factor,float(j)/scale_factor]

from math import floor

P = [floor(float(i)/scale_factor),floor(float(j)/scale_factor)]