Scaling (Resizing) Images - Cubic, Area, Linear Interpolations
Interpolation is a method of estimating values between known data points
# Import Computer Vision package - cv2
import cv2
# Import Numerical Python package - numpy as np
import numpy as np
# Read the image using imread built-in function
image = cv2.imread('image_2.jpg')
# Display original image using imshow built-in function
cv2.imshow("Original", image)
# Wait until any key is pressed
cv2.waitKey()
# cv2.resize(image, output image size, x scale, y scale, interpolation)
# Scaling using cubic interpolation
scaling_cubic = cv2.resize(image, None, fx=.75, fy=.75, interpolation = cv2.INTER_CUBIC)
# Display cubic interpolated image
cv2.imshow('Cubic Interpolated', scaling_cubic)
# Wait until any key is pressed
cv2.waitKey()
# Scaling using area interpolation
scaling_skewed = cv2.resize(image, (600, 300), interpolation = cv2.INTER_AREA)
# Display area interpolated image
cv2.imshow('Area Interpolated', scaling_skewed)
# Wait until any key is pressed
cv2.waitKey()
# Scaling using linear interpolation
scaling_linear = cv2.resize(image, None, fx=0.5, fy=0.5, interpolation = cv2.INTER_LINEAR)
# Display linear interpolated image
cv2.imshow('Linear Interpolated', scaling_linear)
# Wait until any key is pressed
cv2.waitKey()
# Close all windows
cv2.destroyAllWindows()
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