p7happlied = util.applyMask(dft_brain, p7hmask)
p7himage = util.getImage(p7happlied)
p7hfimage = util.post_process_image(p7himage)
filename = "p7_GHP_Masked_Image_" + str(k) + ".jpg"
util.saveImage(filename, p7hfimage)
noisy = util.loadMatrix("images/noisyimage.npy")
noisy_2 = noisy.real.astype(np.complex128)
noisy_image = util.getImage(noisy_2)
noisyfi = util.post_process_image(noisy_image)
#util.displayImage(noisyfi)
noisy_2_write = util.writableDFT(noisy_2)
#util.displayImage_plt(noisy_2_write)
height_noisy, width_noisy = noisy_2.shape
noisy_size = np.array([height_noisy, width_noisy])
p8mask1 = noise.butterworthLowpassFilter(noisy_size, 99, 100)
p8mask2 = noise.gaussianLowpassFilter(noisy_size, 50)
p8mask3 = noise.idealLowpassFilter(noisy_size, 99)
p8applied1 = util.applyMask(noisy_2, p8mask1)
p8applied2 = util.applyMask(noisy_2, p8mask2)
p8applied3 = util.applyMask(noisy_2, p8mask3)
p8image1 = util.getImage(p8applied1)
p8image2 = util.getImage(p8applied2)
p8image3 = util.getImage(p8applied3)
p8fimage1 = util.post_process_image(p8image1)
p8fimage2 = util.post_process_image(p8image2)
p8fimage3 = util.post_process_image(p8image3)
util.saveImage("p8_Buttersworth_99_100.jpg", p8fimage1)
util.saveImage("p8_Gaussian_50.jpg", p8fimage1)
util.saveImage("p8_Ideal_99.jpg", p8fimage1)
# count = 0
# for cut in cutout:
# print(cut)
# mask = isn.gaussianHighpassFilter(mask_size2, cut)
# a = util.applyMask(img_copy, mask)
# b = util.writableDFT(a)
# c = util.normalizeImage(b)
# d = util.post_process_image(c)
# count += 1
# print(count)
# util.displayImage(d)
nmask_size = (h2, w2)
img_copy = util.getImage(img3)
mask = isn.idealHighpassFilter(nmask_size, 100)
mask1 = isn.idealLowpassFilter(nmask_size, 100)
mask2 = isn.gaussianHighpassFilter(nmask_size, 100)
mask3 = isn.ringLowpassFilter(nmask_size, 100, 10)
mask4 = isn.butterworthHighpassFilter(nmask_size, 50, 2)
masks = (mask, mask1, mask2, mask3, mask4)
count = 0
for mask in masks:
a = util.applyMask(mask, img_copy)
count += 1
print(count)
util.displayImage(a)
def test_idealLowpassFilter_half_width(self):
expected = self.setup.getExpectedOutput(self._testMethodName)
self.actual = noise.idealLowpassFilter(self.emptymask, 100)
self.actual = self.setup.normalizeImage(self.actual)
self.assertTrue(self.setup.imagesEqual(expected, self.actual))