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

Contenido del Curso

Computer Vision Course Outline

Computer Vision Course Outline

1. Introduction to Computer Vision
2. Image Processing with OpenCV
3. Convolutional Neural Networks

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).

Tarea

Swipe to start coding

Your task is to apply two types of blur on the noised 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.

Solución

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 2. Capítulo 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).

Tarea

Swipe to start coding

Your task is to apply two types of blur on the noised 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.

Solución

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 2. Capítulo 4
Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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