DeepAI AI Chat
Log In Sign Up

Packet Compressed Sensing Imaging (PCSI): Robust Image Transmission over Noisy Channels

by   Scott Howard, et al.

Packet Compressed Sensing Imaging (PCSI) is digital unconnected image transmission method resilient to packet loss. The goal is to develop a robust image transmission method that is computationally trivial to transmit (e.g., compatible with low-power 8-bit microcontrollers) and well suited for weak signal environments where packets are likely to be lost. In other image transmission techniques, noise and packet loss leads to parts of the image being distorted or missing. In PCSI, every packet contains random pixel information from the entire image, and each additional packet received (in any order) simply enhances image quality. Satisfactory SSTV resolution (320x240 pixel) images can be received in  1-2 minutes when transmitted at 1200 baud AFSK, which is on par with analog SSTV transmission time. Image transmission and reception can occur simultaneously on a computer, and multiple images can be received from multiple stations simultaneously - allowing for the creation of "image nets." This paper presents a simple computer application for Windows, Mac, and Linux that implements PCSI transmission and reception on any KISS compatible hardware or software modem on any band and digital mode.


Predictive refinement methodology for compressed sensing imaging

The weak-ℓ^p norm can be used to define a measure s of sparsity. When we...

Fundamental Limits of Covert Packet Insertion

Covert communication conceals the existence of the transmission from a w...

High-speed Millimeter-wave 5G/6G Image Transmission via Artificial Intelligence

Artificial Intelligence (AI) has been used to jointly optimize a mmWave ...

Identifying Packet Loss and Reordering Packets in Keyed UDP Transmissions

The User Datagram Protocol (UDP) and other similar protocols send the ap...

Spatially Scalable Compressed Image Sensing with Hybrid Transform and Inter-layer Prediction Model

Compressive imaging is an emerging application of compressed sensing, de...

DFTS2: Simulating Deep Feature Transmission Over Packet Loss Channels

In edge-cloud collaborative intelligence (CI), an unreliable transmissio...

ECCR: Edge-Cloud Collaborative Recovery for Low-Power Wide-Area Networks interference mitigation

Recent advances in Low-Power Wide-Area Networks have mitigated interfere...