Vervagen om ruis te verminderen

In deze oefening verlaag je de scherpte van een foto van een gebouw, gemaakt tijdens een trip naar Londen, met behulp van filtering.

Building in Lodon

Afbeelding is geladen als building_image.

Deze oefening maakt deel uit van de cursus

Beeldverwerking in Python

Cursus bekijken

Oefeninstructies

Importeer het Gaussian-filter.
Pas het filter toe op building_image en zet de parameter multichannel op de juiste waarde.
Toon de oorspronkelijke building_image en de resulterende gaussian_image.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Import Gaussian filter 
____

# Apply filter
gaussian_image = ____

# Show original and resulting image to compare
show_image(____, "Original")
____(____, "Reduced sharpness Gaussian")

Code bewerken en uitvoeren

Deze oefening maakt deel uit van de cursus

Beeldverwerking in Python

SkillTag.level.intermediateSkillTag.label

4.8+

Begin de cursus gratis

Jump into digital image structures and learn to process them! Extract data, transform and analyze images using NumPy and Scikit-image. With just a few lines of code, you will convert RGB images to grayscale, get data from them, obtain histograms containing very useful information, and separate objects from the background!

Exercise 1: Make images come alive with scikit-image Exercise 2: Is this gray or full of color?Exercise 3: RGB to grayscale Exercise 4: NumPy for images Exercise 5: Flipping out Exercise 6: Histograms Exercise 7: Getting started with thresholding Exercise 8: Apply global thresholding Exercise 9: When the background isn't that obvious Exercise 10: Trying other methods Exercise 11: Apply thresholding

You will learn to <strong>detect object shapes</strong> using edge detection filters, <strong>improve medical images</strong> with contrast enhancement <strong>and even enlarge pictures to five times its original size! </strong> You will also apply morphology to make thresholding more accurate when segmenting images and go to the next level of processing images with Python.

Exercise 1: Aan de slag met filters Exercise 2: Randdetectie Exercise 3: Vervagen om ruis te verminderen

Huidige oefening

Exercise 4: Contrastverbetering Exercise 5: Wat is het contrast van deze afbeelding?Exercise 6: Medische beelden Exercise 7: Luchtfoto Exercise 8: Laten we wat impact en contrast toevoegen Exercise 9: Transformaties Exercise 10: Aliasing, roteren en herschalen Exercise 11: Afbeeldingen vergroten Exercise 12: Proportioneel resizen Exercise 13: Morfologie Exercise 14: Handgeschreven letters Exercise 15: Drempelbeeld verbeteren

So far, you have done some very cool things with your image processing skills! In this chapter, you will apply <strong>image restoration to remove objects, logos, text, or damaged areas</strong> in pictures! You will also learn how to apply noise, use segmentation to speed up processing, and find elements in images by their contours.

Exercise 1: Image restoration Exercise 2: Let's restore a damaged image Exercise 3: Removing logos Exercise 4: Noise Exercise 5: Let's make some noise!Exercise 6: Reducing noise Exercise 7: Reducing noise while preserving edges Exercise 8: Superpixels & segmentation Exercise 9: Number of pixels Exercise 10: Superpixel segmentation Exercise 11: Finding contours Exercise 12: Contouring shapes Exercise 13: Find contours of an image that is not binary Exercise 14: Count the dots in a dice's image

After completing this chapter, you will have a deeper knowledge of image processing as you will be able to <strong>detect edges, corners, and even faces! </strong> You will learn how to detect not just front faces but also face profiles, cat, or dogs. You will apply your skills to more complex <strong>real-world applications.</strong> Learn to master several widely used image processing techniques with very few lines of code!

Exercise 1: Finding the edges with Canny Exercise 2: Edges Exercise 3: Less edgy Exercise 4: Right around the corner Exercise 5: Perspective Exercise 6: Less corners Exercise 7: Face detection Exercise 8: Is someone there?Exercise 9: Multiple faces Exercise 10: Segmentation and face detection Exercise 11: Real-world applications Exercise 12: Privacy protection Exercise 13: Help Sally restore her graduation photo Exercise 14: Amazing work!