shafeeqahameds / implementation-of-filters

Implementation-of-Filters

Aim:

To implement filters for smoothing and sharpening the images in the spatial domain.

Software Required:

Anaconda - Python 3.7

ALGORITHM:

Step 1:

Import the necessary modules.

Step 2:

Perform smoothing operation on a image.

• Average filter(Box Filter)
• Weighted average filter
• Gaussian Blur
• Median filter

Step 3:

Perform sharpening on a image.

• Laplacian Kernel
• Laplacian Operator

Step 4:

Display all the images with their respective filters.

Program:

Developed By: Shafeeq Ahamed. S

Register Number: 212221230092

1. Smoothing Filters

i) Using Averaging Filter

kernal = np.ones((11,11),np.float32)/121
img_box_filter = cv2.filter2D(img_rgb,-1,kernal)

cv2.imshow("Box Filter",img_box_filter)
cv2.waitKey(0)
cv2.destroyAllWindows()

plt.title("Box")
plt.imshow(img_box_filter)
plt.show()

ii) Using Weighted Averaging Filter

kernal_weighted_avg = np.array([[2,2,2],[4,8,4],[2,4,2]])/15
img_w_avg_filter = cv2.filter2D(img_rgb,-1,kernal_weighted_avg)

cv2.imshow("Weighted Avg Filter",img_w_avg_filter)
cv2.waitKey(0)
cv2.destroyAllWindows()

plt.title("W-Avg")
plt.imshow(img_w_avg_filter)
plt.show()

iii) Using Gaussian Filter

img_gaussian = cv2.GaussianBlur(src = img_rgb, ksize = (11,11), sigmaX=0,sigmaY=0)

cv2.imshow("Gaussian Filter",img_gaussian)
cv2.waitKey(0)
cv2.destroyAllWindows()

plt.title("Gaussian")
plt.imshow(img_gaussian)
plt.show()

iv) Using Median Filter

img_median = cv2.medianBlur(src = img_rgb, ksize = 7)

cv2.imshow("Median Filter",img_median)
cv2.waitKey(0)
cv2.destroyAllWindows()

plt.title("Median")
plt.imshow(img_median)
plt.show()

2. Sharpening Filters

i) Using Laplacian Kernal

kernal_Laplacian = np.array([[1,2,1],[1,-5,1],[2,1,0]])
img_laplacian_kernal = cv2.filter2D(img_rgb,-1,kernal_Laplacian)

cv2.imshow("Laplacian Filter",img_laplacian_kernal)
cv2.waitKey(0)
cv2.destroyAllWindows()

plt.title("Laplacian Kernal")
plt.imshow(img_laplacian_kernal)
plt.show()

ii) Using Laplacian Operator

img_laplacian = cv2.Laplacian(img_rgb,cv2.CV_64F)

cv2.imshow("Laplacian",img_laplacian)
cv2.waitKey(0)
cv2.destroyAllWindows()

plt.title("Laplacian Operator")
plt.imshow(img_laplacian)
plt.show()

OUTPUT:

1. Smoothing Filters

i) Using Averaging Filter

Original	Averaging Filter

ii) Using Weighted Averaging Filter

Original	Weighted Averaging Filter

iii) Using Gaussian Filter

Original	Gaussian Filter

iv) Using Median Filter

Original	Median Filter

2. Sharpening Filters

i) Using Laplacian Kernal

Original	Laplacian Kernal

ii) Using Laplacian Operator

Original	Laplacian Operator

Result:

Thus the filters are designed for smoothing and sharpening the images in the spatial domain.