Finish first two without edge (eaae4cb6) · Commits · 袁通 / EE326 Digital Image Processing LAB

Lab2_Image_Interpolation/bicubic_11810818.py

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		@@ -8,7 +8,12 @@ Shrink: [205, 205]

		import numpy as np
		from skimage import io, data
		import math
		from scipy import interpolate

		def small_map2(x, range):
		ratio = x/range
		return 3.01 + ratio*(range-8.02)

		def bicubic_11810818(input_file, dim):
		# Load image
		@@ -20,8 +25,19 @@ def bicubic_11810818(input_file, dim):
		out_image = np.zeros(dim, dtype=np.uint8)

		# Perform Exchange
		for col in range(out_width):
		for row in range(out_height):
		pix_x = small_map2(col*((in_width-1)/(out_width-1)), out_width)
		pix_y = small_map2(row*((in_height-1)/(out_height-1)), out_height)
		x=[math.floor(pix_x)-1, math.floor(pix_x), math.floor(pix_x)+1, math.floor(pix_x)+2]
		y=[math.floor(pix_y)-1, math.floor(pix_y), math.floor(pix_y)+1, math.floor(pix_y)+2]
		z=in_image[math.floor(pix_x)-1:math.floor(pix_x)+3, math.floor(pix_y)-1:math.floor(pix_y)+3]
		f = interpolate.interp2d(x, y, z, kind='cubic')

		out_image[col, row] = f(col, row)

		# Save Image
		print(out_image)
		io.imsave("bicubic_11810818.tif", out_image)

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		@@ -39,7 +39,11 @@ def bilinear2_11810818(input_file, dim):
		y = small_map(row*((in_height-1)/(out_height-1)), out_height)
		left=linear(y-math.floor(y), in_image[math.floor(x), math.floor(y)], in_image[math.floor(x), math.floor(y)+1])
		right=linear(y-math.floor(y), in_image[math.floor(x)+1, math.floor(y)], in_image[math.floor(x)+1, math.floor(y)+1])
		out_image[col, row] = round(linear(x-math.floor(x), right, left))
		horizontal=linear(x-math.floor(x), left, right)
		top=linear(x-math.floor(x), in_image[math.floor(x), math.floor(y)], in_image[math.floor(x)+1, math.floor(y)])
		bottom=linear(x-math.floor(x), in_image[math.floor(x), math.floor(y)+1], in_image[math.floor(x)+1, math.floor(y)+1])
		vertical=linear(y-math.floor(y), top, bottom)
		out_image[col, row] = round(0.5*(vertical+horizontal))

		print(out_image)
		# Save Image

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		"""
		LAB2 Task 1_2

		Use bilinear interpolation interpolation to interpolate a grey scale image
		Enlarge: [461, 461]
		Shrink: [205, 205]
		"""

		import numpy as np
		from skimage import io, data
		import math


		def linear(x, y1, y2):
		if y2 > y1:
		return y1 + x * (y2-y1)
		else:
		return y2 + (1-x)*(y1-y2)


		def small_map(x, range):
		ratio = x/range
		return 0.01 + ratio*(range-0.02)


		def bilinear3_11810818(input_file, dim):
		# Load image
		in_image = io.imread(input_file)
		print(in_image)
		out_width = dim[0]
		out_height = dim[1]
		in_width = in_image.shape[0]
		in_height = in_image.shape[1]
		out_image = np.zeros(dim, dtype=np.uint8)
		# out_image = np.zeros(dim)

		# Perform Exchange
		for col in range(out_width):
		for row in range(out_height):
		x = small_map(col*((in_width-1)/(out_width-1)), out_width)
		y = small_map(row*((in_height-1)/(out_height-1)), out_height)

		left=linear(y-math.floor(y), in_image[math.floor(x), math.floor(y)], in_image[math.floor(x), math.floor(y)+1])
		right=linear(y-math.floor(y), in_image[math.floor(x)+1, math.floor(y)], in_image[math.floor(x)+1, math.floor(y)+1])

		out_image[col, row] = round(linear(x-math.floor(x), left, right))

		# Save Image
		io.imsave("shrank_bilinear_11810818.tif", out_image)


		if __name__ == '__main__':
		bilinear3_11810818("rice.tif", [205, 205])
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