Wand wavelet_denoise() function – Python

The wavelet_denoise() function is an inbuilt function in the Python Wand ImageMagick library which is used to remove noise by applying a wavelet transform.

Syntax:

wavelet_denoise(threshold, softness)

Parameters: This function accepts two parameters as mentioned above and defined below: 

• Threshold: This parameter stores the value of the smoothing limit.
• Softness: This parameter stores the value of the amount of attenuation of the smoothing threshold..

Return Value: This function returns the Wand ImageMagick object.

Original Image:

Example 1:

Python3

# Import library from Image
from wand.image import Image

# Import the image
with Image(filename ='../geeksforgeeks.png') as image:
    # Clone the image in order to process
    with image.clone() as wavelet_denoise:
        # Invoke wavelet_denoise function with threshold as 10
        # softness as 15
        wavelet_denoise.wavelet_denoise(10, 15)
        # Save the image
        wavelet_denoise.save(filename ='wavelet_denoise1.jpg')

Output:

Example 2:

Python3

# Import libraries from the wand
from wand.image import Image
from wand.drawing import Drawing
from wand.color import Color

with Drawing() as draw:
    # Set Stroke color the circle to black
    draw.stroke_color = Color('black')
    # Set Width of the circle to 2
    draw.stroke_width = 1
    # Set the fill color to 'White (# FFFFFF)'
    draw.fill_color = Color('white')

    # Invoke Circle function with center at 50, 50 and radius 25
    draw.circle((200, 200), # Center point
                (100, 100)) # Perimeter point
    # Set the font style
    draw.font = '../Helvetica.ttf'
    # Set the font size
    draw.font_size = 30

    with Image(width = 400, height = 400, background = Color('# 45ff33')) as pic:
        # Set the text and its location
        draw.text(int(pic.width / 3), int(pic.height / 2), 'GeeksForGeeks !')
        # Draw the picture
        draw(pic)
        # Invoke wavelet_denoise function with threshold as 20
        # softness as 10
        pic.wavelet_denoise(20, 10)
        # Save the image
        pic.save(filename ='wavelet_denoise2.jpg')

Output: