Resilient image sensor networks in lossy channels using compressed sensing

—Data loss in wireless communications greatly affects the reconstruction quality of a signal. In the case of images, data loss results in a reduction in quality of the received image. Conventionally, channel coding is performed at the encoder to enhance recovery of the signal by adding known redundancy. While channel coding is effective, it can be very computationally expensive. For this reason, a new mechanism of handling data losses in Wireless Multimedia Sensor Networks (WMSN) using Compressed Sensing (CS) is introduced in this paper. This system uses compressed sensing to detect and compensate for data loss within a wireless network. A combination of oversampling and an adaptive parity scheme are used to determine which CS samples contain bit errors, remove these samples and transmit additional samples to maintain a target image quality A study was done to test the combined use of adaptive parity and compressive oversampling to transmit and correctly recover image data in a lossy...

• Type: Journal
• Year: 2010
• Where: PERCOM
• Authors: Scott Pudlewski, Arvind Prasanna, Tommaso Melodia
• Keywords: Compressed Sensing, Computer Networks, Data Loss, Images, PERCOM 2010