Bound-Conditioned Latent Inference for Progressive Image Compression

Bound-Conditioned Latent Inference (BLI) redefines progressive trit-plane coding as sequential latent inference under shrinking interval constraints, using decoded trits to set lower and upper bounds for each latent element. BLI jointly refines Gaussian parameters and latent estimates with hyperprior information, enabling tighter constraints and flexible refinement schedules. Experiments on Kodak, CLIC, and JPEG-AI demonstrate state‑of‑the‑art rate‑distortion performance, reducing BD‑rate by 17.78% over DPICT and 7.96% over CTC while using far fewer parameters and lower latency.

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