Write program to perform spatial filtering of an image You

Write program to perform spatial filtering of an image . You can fix the size of the spatial mask at 3 x 3, but the coefficients need to be variables that can be input into your program.(matlab program)

def spatial_filtering(i, j):

# create a s*s array to represent the pixels that have

# influence on position(i,j)\'s new grey level

array = [[(0,0)] * s ] * s

average = 0

# count the coordinate of the s*s pixels

for a in range(s):

for b in range(s):

x = i + dis[a]

y = j + dis[b]

# if the pixel\'s position is out of the image\'s range

# set it to the boundary\'s value

if(x < 0):

x = 0

if(y < 0):

y = 0

if(x >= width):

x = width - 1

if(y >= height):

y = height - 1

# keep the array for better understanding, it can be deleted

array[a][b] = ( x, y )

#count the average of the s*s pixels\' grey level

average += data[array[a][b]]

average = average / (s * s)

#return average

return average

# open an image and get its information

im = Image.open(\'Fig0219(rose1024).tif\')

data = im.load()

width, height = im.size

MN = width * height

# new two blank images for rewrite and downsampling

resultImage = Image.new(\'L\',(width, height), \'white\')

# count the frequency of each grey level

s = input(\'please input size: \')

dis = [0] * s

for c in range(s):

dis[c] = c - (s / 2)

# draw the new HE image

draw = ImageDraw.Draw(resultImage)

#width = height = 10

for i in range(width):

for j in range(height):

# for each pixel, find its corresponding grey level after HE

p = spatial_filtering(i, j)

draw.point((i, j), p)

filename = \'SFImage_rose_blursize=\' + str(s) + \'.bmp\'

#save the output files

resultImage.save(filename, format=\'BMP\')