Hardware Acceleration of Image Registration Algorithm on FPGA-based Systems on Chip

Image processing algorithms are dominating contemporary digital systems due to their importance and adoption by a large number of application domains. Despite their significance, their computational requirements often limit their usage, especially in deeply embedded designs. Heterogeneous computing systems offer a promising solution for this performance gap, leading to their ever increasing utilization by designers. This work targets the acceleration of an image registration pipeline on a System-on-Chip (SoC) including both general purpose and re-configurable computing elements. The evaluation of our proposed HW/SW co-designed image registration application on a state-of-the-art FPGA based SoC showcases its ability to outperform software designs leading to orders of performance speedup (up to 67x) against embedded CPUs.

[1]  William H. Press,et al.  Numerical Recipes 3rd Edition: The Art of Scientific Computing , 2007 .

[2]  Junying Chen,et al.  Design considerations of real-time adaptive beamformer for medical ultrasound research using FPGA and GPU , 2012, 2012 International Conference on Field-Programmable Technology.

[3]  Ntana Nkanza,et al.  Image Registration and its Application to Computer Vision: Mosaicing and Independent Motion detection , 2005 .

[4]  Shuvra S. Bhattacharyya,et al.  Model-based mapping of reconfigurable image registration on FPGA platforms , 2008, Journal of Real-Time Image Processing.

[5]  Thomas Ertl,et al.  Computer Graphics - Principles and Practice, 3rd Edition , 2014 .

[6]  Brandyn White,et al.  Using FPGAs to perform embedded image registration , 2009 .

[7]  M. Carter.  Computer graphics: Principles and practice , 1997 .

[8]  Alan C. Evans,et al.  3-D Brain MRI Tissue Classification on FPGAs , 2009, IEEE Transactions on Image Processing.

[9]  Donald G. Bailey,et al.  Design for Embedded Image Processing on FPGAs , 2011 .

[10]  Kidiyo Kpalma,et al.  An automatic image registration for applications in remote sensing , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Donald G. Bailey,et al.  Design for Embedded Image Processing on FPGAs: Bailey/Design for Embedded Image Processing on FPGAs , 2011 .

[12]  John A. Stankovic,et al.  Research Directions for the Internet of Things , 2014, IEEE Internet of Things Journal.

[13]  Darshana Mistry,et al.  Survey of Image Registration techniques for Satellite Images , 2022 .

[14]  Stanley R. Sternberg,et al.  Biomedical Image Processing , 1983, Computer.

[15]  Dimitrios Soudris,et al.  A survey on reconfigurable accelerators for cloud computing , 2016, 2016 26th International Conference on Field Programmable Logic and Applications (FPL).

[16]  J.M. Jagadeesh,et al.  FAIR: a hardware architecture for real-time 3-D image registration , 2003, IEEE Transactions on Information Technology in Biomedicine.

[17]  Lawrence A. Ray,et al.  2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications , 2005, J. Electronic Imaging.

[18]  Raj Shekhar,et al.  FPGA-Accelerated Deformable Image Registration for Improved Target-Delineation During CT-Guided Interventions , 2007, IEEE Transactions on Biomedical Circuits and Systems.

[19]  Julie H. Simpson,et al.  BrainAligner: 3D Registration Atlases of Drosophila Brains , 2011, Nature Methods.

[20]  Igor V. Maslov,et al.  Automatic image registration and target recognition with multiresolution hybrid evolutionary algorithm , 2004, SPIE Defense + Commercial Sensing.

[21]  Konstantina S. Nikita,et al.  Automatic retinal image registration scheme using global optimization techniques , 1999, IEEE Transactions on Information Technology in Biomedicine.

[22]  Thomas Martin Deserno.  Comprar Biomedical Image Processing | Deserno, Thomas Martin | 9783642158155 | Springer , 2011 .

[23]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[24]  Rodney A. Kennedy,et al.  A Survey of Medical Image Registration on Multicore and the GPU , 2010, IEEE Signal Processing Magazine.

[25]  Jung A Kim.  The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care , 2011 .

[26]  Mohd Fauzi Bin Othman,et al.  An overview of MRI brain classification using FPGA implementation , 2010, 2010 IEEE Symposium on Industrial Electronics and Applications (ISIEA).