Overlapped block-based compressive sensing imaging on mobile handset devices

  • Henry Aguello-Fuentes Universidad Industrial de Santander
  • Irene Lizeth Manotas-Gutiérrez Universidad Industrial de Santander
Keywords: Compressive sensing, algoritmos de reconstrucción, dispositivos móviles


Compressive Sensing (CS) is a new technique that simultaneously senses and compresses an image by taking a set of random projections from the underlying scene. An optimization algorithm is then used to recover the initial image. In practice, these optimization algorithms have restricted CS techniques to be implemented on high performance computational architectures, such as personal computers or graphical processing units (GPU) due the huge number of operations required for the image recovery. This work extends the application of CS to be implemented in an extremely limited memory and processing architecture such as a mobile device. Specifically, overlapped blocking-based algorithms are developed such that it is possible to reconstruct an image on a mobile device. An analysis of the energy consumption of the block-based CS algorithms is presented. The results show the required computational time for reconstruction and the image reconstruction quality for images of 128x128 and 256x256 pixels.

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Author Biographies

Henry Aguello-Fuentes, Universidad Industrial de Santander

Profesor Asociado

Escuela de Ingeniería de Sistemas e Informática, Departamento de Sistemas e Informática


Irene Lizeth Manotas-Gutiérrez, Universidad Industrial de Santander

Departamento de Ingeniería de Sistemas e Informática


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How to Cite
Aguello-Fuentes H., & Manotas-Gutiérrez I. L. (2014). Overlapped block-based compressive sensing imaging on mobile handset devices. Revista Facultad De Ingeniería Universidad De Antioquia, (70), 173-184. Retrieved from https://revistas.udea.edu.co/index.php/ingenieria/article/view/15284