Probabilistic Principal Component Analysis and Channel Attention for End-to-End Image Compression Optimization

Probabilistic Principal Component Analysis and Channel Attention for End-to-End Image Compression Optimization

In recent years, deep learning has shown significant progress for image compression compared to traditional image compression methods. Although conventional standard-based methods are still used, they are limited in handling repetitive patterns and complex calculations, which can lead to image recon...

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Bibliographic Details
Main Authors: Andri Agustav Wirabudi, Sung-Chang Lim, Woong Lim, Jeongil Seo, Haechul Choi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Attention mechanisms
autoencoder
image compression
probabilistic principal component analysis
quality assessment
Online Access:https://ieeexplore.ieee.org/document/11072174/
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https://ieeexplore.ieee.org/document/11072174/

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