import numpy as np
from matplotlib import pyplot as plt
from Filter import applyFilter
plt.figure(figsize=(12, 12))
im = cv2.imread("inp1.tif", 0).astype(np.float)
#creating gaussian filter
gaussianFilter = np.array(
[[1, 1, 2, 2, 2, 1, 1], [1, 2, 2, 4, 2, 2, 1], [2, 2, 4, 8, 4, 2, 2],
[2, 4, 8, 16, 8, 4, 2], [2, 2, 4, 8, 4, 2, 2], [1, 2, 2, 4, 2, 2, 1],
[1, 1, 2, 2, 2, 1, 1]], np.float)
gaussianFilter /= np.sum(gaussianFilter * 1.0)
#applying gaussian filter
output = applyFilter(im, imFilter=gaussianFilter)
#writing image to image file
cv2.imwrite("gaussian.jpg", output)
#plotting original image
plt.subplot(211)
plt.axis('off')
plt.title("Original Image")
plt.imshow(im, cmap="gray")
#plotting smoothed image
plt.subplot(212)
plt.axis('off')
plt.title("Smoothed Image (gaussian filter7x7 (sigma 1.4))")
plt.imshow(output, cmap="gray")
plt.show()
from Filter import applyFilter
plt.figure(figsize=(12, 12))
#reading image from file
im = cv2.imread("inp1.tif", 0).astype(np.float)
#creating weighted filter:
#[1 2 1],
#[2 4 2],
#[1 2 1]
weightedFilter = (1.0 / 16) * np.array([[1, 2, 1], [2, 4, 2], [1, 2, 1]],
np.int32)
#applying filter on image
output = applyFilter(im, imFilter=weightedFilter)
#writing image to image file
cv2.imwrite("weightedavg.jpg", output)
#plotting original image
plt.subplot(211)
plt.axis('off')
plt.title("Original Image")
plt.imshow(im, cmap="gray")
#plotting smoothed image
plt.subplot(212)
plt.axis('off')
plt.title("Smoothed Image (weighted avg. filter3x3)")
plt.imshow(output, cmap="gray")
import cv2
import numpy as np
from matplotlib import pyplot as plt
from Filter import applyFilter
plt.figure(figsize=(12, 12))
#reading image from file
im = cv2.imread("inp1.tif", 0).astype(np.float)
size = int(raw_input("> Enter the size of averaging filter: "))
#applying filter on image
output = applyFilter(im, filterSize=size)
#writing image to image file
cv2.imwrite("averaging.jpg", output)
#plotting original image
plt.subplot(211)
plt.axis('off')
plt.title("Original Image")
plt.imshow(im, cmap="gray")
#plotting smoothed image
plt.subplot(212)
plt.axis('off')
plt.title("Smoothed Image (avg. filter" + str(size) + "x" + str(size) + ")")
plt.imshow(output, cmap="gray")
plt.show()
def unsharpMasking(img):
inputImg = copy.deepcopy(img)
blurredImg = applyFilter(inputImg, filterSize=5)
mask = inputImg - blurredImg
result = inputImg + mask
return result