Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration

• URL: http://arxiv.org/abs/2406.07435v1
• Date: Tue, 11 Jun 2024 16:42:17 GMT
• Title: Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration
• Authors: Shashank Agnihotri, Julia Grabinski, Janis Keuper, Margret Keuper,
• Abstract summary: We show that simply providing alias-free paths in state-of-the-art reconstruction transformers supports improved model robustness at low costs on the restoration performance. We do so by proposing BOA-Restormer, a transformer-based image restoration model that executes downsampling and upsampling operations partly in the frequency domain to ensure alias-free paths along the entire model while potentially preserving all relevant high-frequency information.
• Score: 20.607361871965157
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Image restoration networks are usually comprised of an encoder and a decoder, responsible for aggregating image content from noisy, distorted data and to restore clean, undistorted images, respectively. Data aggregation as well as high-resolution image generation both usually come at the risk of involving aliases, i.e.~standard architectures put their ability to reconstruct the model input in jeopardy to reach high PSNR values on validation data. The price to be paid is low model robustness. In this work, we show that simply providing alias-free paths in state-of-the-art reconstruction transformers supports improved model robustness at low costs on the restoration performance. We do so by proposing BOA-Restormer, a transformer-based image restoration model that executes downsampling and upsampling operations partly in the frequency domain to ensure alias-free paths along the entire model while potentially preserving all relevant high-frequency information.

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