# import necessary packages

# reading$/$writing image files

from skimage import io

from skimage import color

# array operations

import numpy as np

# displaying images and plots

import matplotlib as mpl

import matplotlib.pyplot as plt

# mathematical calculations

import math

# signal processing operations

from scipy import signal

# random number generation

from scipy.stats import norm

# DFT calculations

from scipy import fftpack as ft

# STEP $3$ Estimate the power spectrum of the observed $($blurred and noisy$)$ image

# ADD YOUR CODE HERE

# for every $64$x$64$ block of the observed image:

# window the block with a Hanning window $($use a taper length of $6)$

# my$\_$winHanning$($nSize$,$ nTaper$)$:

# take the DFT of each block

# calculate the magnitude$-$squared of DFT$\text{'}$s

# obtain P$\_$g$($k$,$l$)$ as the average over the blocks $($there should be $64$ blocks$)$

def my$\_$winHanning$($nSize$,$ nTaper$)$:

assert nTaper $>0$

assert nSize $>2*$ nTaper

# create an array to hold the window

winHann $=$ np$.$ones$($nSize$)$

# taper left and right sides

val $=$ math.pi $/$ nTaper

for n in range$($nTaper$)$:

# calculate taper

w $=0\mathrm{.}5+0\mathrm{.}5*$ math.cos$($n $*$ val$)$

# assign right taper

winHann$[$nSize $-$ nTaper $+$ n$]=$ w

# assign left taper

winHann$[$nTaper $-1-$ n$]=$ w

return winHann

height, width $=$ imgBlurredNoisy.shape

block$\_$size $=64$

taper$\_$length$=6$

power$\_$spectrum$\_$total$=0$

num$\_$blocks$=0$

for i in range$(0,$ height, block$\_$size$)$:

for j in range$(0,$ width, block$\_$size$)$:

img$\_$block $=$ imgBlurredNoisy$[$i:i$+$block$\_$size, j:j$+$block$\_$size$]$

window $=$ my$\_$winHanning$($block$\_$size, taper$\_$length$)$

windowed$\_$block $=$ img$\_$block $*$ window

fft$\_$block $=$ ft$.$fft$2($windowed$\_$block$)$

power$\_$spectrum $=$ np$.$abs$($fft$\_$block$)**2$

power$\_$spectrum$\_$total $+=$ power$\_$spectrum

num$\_$blocks $+=1$

P$\_$g $=$ power$\_$spectrum$\_$total $/$ num$\_$blocks The image is $256$x$256.$ I get $64$x$64$ where I should get $4$x$4$ matrix. Could you explain why and fix the code? Thank you.