@inproceedings{4684873018404c85a19a0452e9570e67,
title = "Spatially adaptive and flexible deep network for blind compressed image reconstruction",
abstract = "JPEG is the most widely used image compression format, but low quality factors introduce blocking and ringing artifacts that degrade visual quality and hinder computer vision tasks. Existing deep learning methods often require separate models for different compression levels, whereas FBCNN (flexible blind convolutional neural network) handles multiple qualities with a single model but remains limited by ResNet (deep residual learning networks)-based blocks (ResBlocks) in capturing diverse features. To address this, we propose SA-FBCNN (a Spatially Adaptive Flexible Blind deep Convolutional Neural Network) that enhances feature extraction across regions and scales. With lower model complexity, our framework achieves superior quantitative and qualitative JPEG image reconstruction performance.",
keywords = "Image restoration, JPEG image compression, deep learning., image reconstruction, quality factor prediction",
author = "Yen, \{Po Yu\} and Kang, \{Li Wei\}",
note = "Publisher Copyright: {\textcopyright} 2026 SPIE.; International Workshop on Advanced Imaging Technology, IWAIT 2026 ; Conference date: 12-01-2026 Through 14-01-2026",
year = "2026",
month = feb,
day = "27",
doi = "10.1117/12.3102643",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Masayuki Nakajima and Chuan-Yu Chang and Chien-Chou Lin and Shogo Tokai and Kwang-Deok Seo and Chia-Hung Yeh and Budianto Tandianus",
booktitle = "International Workshop on Advanced Imaging Technology, IWAIT 2026",
}