Block-based compressed sensing has emerged as a newly developed compression technique in the last couple of years. With the concepts from the rate-distortion theory, block-based compressed sensing aims at reducing the distortion while keeping the constant rate. In addition, transmission of compressed data forms an inevitable part in multimedia communications. We would like to explore the error resilient transmission from both the encoder and the decoder. At the encoder, we classify the original image into smooth and active regions, and set the measurement rates adaptively to both regions in order to keep the weighted measurement rate as a constant. At the decoder, we expect there might be effects to compressed media to cause quality degradation to the decoder. And we apply error protection techniques to the smooth and active regions in order to reach the goal of error resilient transmission. Simulation results have demonstrated the effects with adaptive measurement rates, and the capability with the error protection and regression techniques.
Relation:
2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)
