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Oppiskele Noise Reduction and Smoothing | Image Processing with OpenCV
Computer Vision Course Outline
course content

Kurssisisältö

Computer Vision Course Outline

Computer Vision Course Outline

1. Introduction to Computer Vision
2. Image Processing with OpenCV
3. Convolutional Neural Networks
4. Object Detection
5. Advanced Topics Overview

book
Noise Reduction and Smoothing

Noise in images appears as unwanted graininess or distortion, often caused by low lighting, compression artifacts, or sensor limitations. Smoothing techniques help reduce noise while preserving important image details.

Gaussian Blurring (Smoothing Noise)

The Gaussian filter applies a weighted average to surrounding pixels, giving a natural-looking blur.

Median Blurring (Salt-and-Pepper Noise Removal)

The median filter replaces each pixel with the median value of its neighbors. This is effective for removing salt-and-pepper noise (random white and black pixels).

Tehtävä

Swipe to start coding

Apply two types of blur on the noisy image of a puppy: noisy puppy It is to see how the effect differs.

  • Kernel size for Gaussian Blur must be 15x15;
  • Kernel size for Median Blur must be 5.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 2. Luku 4
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book
Noise Reduction and Smoothing

Noise in images appears as unwanted graininess or distortion, often caused by low lighting, compression artifacts, or sensor limitations. Smoothing techniques help reduce noise while preserving important image details.

Gaussian Blurring (Smoothing Noise)

The Gaussian filter applies a weighted average to surrounding pixels, giving a natural-looking blur.

Median Blurring (Salt-and-Pepper Noise Removal)

The median filter replaces each pixel with the median value of its neighbors. This is effective for removing salt-and-pepper noise (random white and black pixels).

Tehtävä

Swipe to start coding

Apply two types of blur on the noisy image of a puppy: noisy puppy It is to see how the effect differs.

  • Kernel size for Gaussian Blur must be 15x15;
  • Kernel size for Median Blur must be 5.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 2. Luku 4
Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Pahoittelemme, että jotain meni pieleen. Mitä tapahtui?
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