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arXiv · 2609.14690

LIMODENet: Attention-Free Compact Encoders for Information-Preserving Onboard Satellite Image Restoration

Thanh-Dung Le·Vu Nguyen Ha·Ti Ti Nguyen·Symeon Chatzinotas
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Abstract

Onboard satellites must restore a channel-degraded image on a few watts, using neuromorphic accelerators (e.g., BrainChip Akida, Intel Loihi-2) that support no softmax or attention. We ask which encoder restores best under that constraint and introduce LIMODENet (LinearMix-ODENet), a 0.69M softmax-/QKV-free backbone whose residual stages read as ODE discretizations and which is empirically information-preserving (probe accuracy rises 79.9% -> 98.4% from stem to head). At iso-parameters it restores 1 dB DVB-S2X-degraded EuroSAT better than a CNN autoencoder (+1.75 dB PSNR) and a skip-connection U-Net (+1.07 dB), three seeds, non-overlapping. Unconstrained modern restorers (NAFNet, Restormer) win on fidelity; we decompose that gap: spiking-legal additive skips recover about half, and the rest traces to attention and channel gating. LIMODENet then converts end-to-end to a spiking network with zero blocked operations, versus 22-24 for the competitors: not the best restorer available, but the best verified deployable within a real power budget.

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Thanh-Dung Le, Vu Nguyen Ha, Ti Ti Nguyen, Symeon Chatzinotas. 2026-09-13. LIMODENet: Attention-Free Compact Encoders for Information-Preserving Onboard Satellite Image Restoration. https://arxiv.org/abs/2609.14690

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