Multi image super resolution using compressed sensing

In this paper we present a new compressed sensing model and reconstruction method for multi-detector signal acquisition. We extend the concept of the famous single-pixel camera to a multidetector device with the benefit of reducing measurement time, while still providing resolution enhancement and deblurring. We provide a scalable model which allows the trade off between system complexity (number of detectors) and time (number of measurements). We test our model on simulated sparse and compressible data and show convergence using the proposed reconstruction method. We also show that our model allows for significant reduction of necessary measurements. A real-live setup for data acquisition according to the new model is presented and we show successful reconstruction of the acquired data. With this setup it is possible to acquire super-resolution images with a low resolution camera. The measurements can also be corrupted by a considerable amount of blurring and noise.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Torsten Edeler, Kevin Ohliger, Stephan Hussmann, Alfred Mertins
• Keywords: ICASSP 2011, Measurements, Model, Reconstruction Method, Signal Processing