def inverse_dct_reduced_coeff(X, coeff):
'''Return the inverse DCT with reduced Coeff'''
mask = masking(coeff)
block_size = (8, 8)
masker = lambda X: np.multiply(X, mask)
dct_recons = dip.block_process(X, masker, block_size)
return dip.block_process(dct_recons, dip.idct_2d, block_size)
def perform_idct(self, F):
return np.asarray(dip.block_process(F, scifft.idctn, (self.bs, self.bs)), np.float64)
def dct(X):
'''Compute 2-D DCT of 8x8 non-overlaping blocks'''
block_size = (8, 8)
return dip.block_process(X, dip.dct_2d, block_size)
def inverse_dct(X):
'''Compute the inverse 2-D DCT of 8x8 non-overlapping blocks'''
block_size = (8, 8)
return dip.block_process(X, dip.idct_2d, block_size)
im_vec)
row, col = im.shape
im_bit_rate = stream_length / (row * col)
# ===================!!!!! DO NOT EDIT THIS PART !!!!!=========================
print("Bit rate of the original image = {:.2f} bits/pixel".format(im_bit_rate))
# STEP 6: Subtract 127
# ============================ EDIT THIS PART =================================
# Change im to a float for computations
im = im.astype(float)
im = im - 127
# STEP 7: Block-wise DCT
block_size = (8, 8)
# ============================ EDIT THIS PART =================================
im_DCT = dip.block_process(im, dip.dct_2d, block_size)
# ===================!!!!! DO NOT EDIT THIS PART !!!!!=========================
dip.subplot(2, 2, 3)
dip.imshow(im_DCT, 'gray')
dip.title(
"Block-wise DCT coefficients - Blocksize = {}x{}".format(*block_size))
# STEP 8: Quantization
c = 1
Q_table = dip.JPEG_Q_table_luminance
# ============================ EDIT THIS PART =================================
quantize = lambda x: x / (c * Q_table)
im_DCT_quantized = dip.block_process(im_DCT, quantize, block_size)
im_DCT_quantized = im_DCT_quantized.astype(int)
# ===================!!!!! DO NOT EDIT THIS PART !!!!!=========================