Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN
Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN
www.fabriziomusacchio.com Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN
In this post, we explore the performance of PCA, Kernel PCA, denoising autoencoder, and CNN for image denoising.
![Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN](https://programming.dev/pictrs/image/5a2ca4f3-b1d4-4417-9c0d-fc0bbd2fd56d.jpeg?format=webp&thumbnail=256)
June 21, 2023 | Fabrizio Musacchio writes:
In this post, we will explore the potential of PCA [Principal Component Analysis], denoising autoencoders and Convolutional Neural Networks (CNN) for restoring noisy images using Python. We will examine their performance, advantages, and disadvantages to determine the most effective method for image denoising.
0
comments