It sends images by adjusting power for each piece based on how much that piece matters.

Sending images from small wireless devices over weak connections is difficult. Traditional methods fail abruptly when the signal drops, while standard neural network approaches struggle to protect small image patches. To solve this, researchers designed a system called TokenComSR. It breaks images into smaller visual pieces called tokens. First, a power allocation tool figures out which image pieces are most critical for sharpness and gives them extra transmission power. Next, a refinement tool checks channel noise and cleans up transmission errors in these tokens before decoding. Finally, a receiver rebuilds and sharpens the image to a higher resolution. Testing showed that this approach effectively protects images, beating older separate coding and existing neural network baselines in both detail accuracy and visual quality.

Why it matters

When you send images over weak wireless signals, like on a phone in a bad area, the picture often breaks completely. This framework keeps images clear by sending important parts more reliably, helping people on low-power devices get better quality without extra data.

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