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GIC-DLC: Differentiable Logic Circuits for Hardware-Friendly Grayscale Image Compression
Simon Bührer, et al., AAAI 2026 Workshop on ML4Wireless, January 2026
Abstract
Neural image codecs compress better than hand-built formats like PNG and JPEG-XL, but they are too expensive for energy-constrained edge devices. GIC-DLC is a grayscale codec that trains lookup-table logic circuits instead, keeping much of the flexibility of a neural network while running as a cheap Boolean circuit. On grayscale benchmarks it compresses better than traditional codecs while using less energy and running faster, which makes it practical for low-power imaging on phones, cameras, and drones.
Tags
- Learned Compression
- Boolean Logic
- Edge AI
- FPGA
- Energy-Efficient Systems