Sharpening images

This piece of code shows how to sharpen a grayscale image (for color images do the same for each channel).
Sharpening is performed by applying a Laplacian operator on the image and adding the output to the original image.

Finally, this is the operator used (Laplacian+image):

-1 -1 -1

-1 9 -1
-1 -1 -1

(see this nice application in which you can perform convolution with the above operator on a given image)

The code (assumes an image named imname is loadable, final output is stored in image named gray):

gray=cvLoadImage(imname,0)

imwidth = gray.rows

imheight = gray.cols

# convert to 32 bit

gray2=cvCreateImage (cvSize (imheight, imwidth), 32, 1)

for r in range(gray.rows):

for c in range(gray.cols):

gray2[r][c]=gray[r][c]

# define the filter:

lapl=cvCreateImage (cvSize (imheight, imwidth), 32, 1)

m=cvCreateImage (cvSize (3,3), 32, 1)

m[0][0]=-1

m[0][1]=-1

m[0][2]=-1

m[2][0]=-1

m[2][1]=-1

m[2][2]=-1

m[1][0]=-1

m[1][2]=-1

m[1][1]=8

cvFilter2D(gray2,lapl,m)

maxv=0

for r in range(gray.rows):

for c in range(gray.cols):

if(lapl[r][c]>maxv):

maxv=lapl[r][c]

for r in range(gray.rows):

for c in range(gray.cols):

v=int(255*lapl[r][c]/maxv)

gray[r][c]=gray[r][c]+v

maxv=0

for r in range(gray.rows):

for c in range(gray.cols):

if(gray[r][c]>maxv):

maxv=gray[r][c]

for r in range(gray.rows):

for c in range(gray.cols):

v=int(255*gray[r][c]/maxv)

gray[r][c]=v