FPGA Based Efficient Multiplier for Image Processing Applications Using Recursive Error Free Mitchell Log Multiplier and KOM Architecture

The Digital Image processing applications like medical imaging, satellite imaging, Biometric trait images etc., rely on multipliers to improve the quality of image. However, existing multiplication techniques introduce errors in the output with consumption of more time, hence error free high speed multipliers has to be designed. In this paper we propose FPGA based Recursive Error Free Mitchell Log Multiplier (REFMLM) for image Filters. The 2x2 error free Mitchell log multiplier is designed with zero error by introducing error correction term is used in higher order Karastuba-Ofman Multiplier (KOM) Architectures. The higher order KOM multipliers is decomposed into number of lower order multipliers using radix 2 till basic multiplier block of order 2x2 which is designed by error free Mitchell log multiplier. The 8x8 REFMLM is tested for Gaussian filter to remove noise in fingerprint image. The Multiplier is synthesized using Spartan 3 FPGA family device XC3S1500-5fg320. It is observed that the performance parameters such as area utilization, speed, error and PSNR are better in the case of proposed architecture compared to existing architectures

[1]  E. V. Krishnamurthy,et al.  On Computer Multiplication and Division Using Binary Logarithms , 1963, IEEE Transactions on Electronic Computers.

[2]  Khalid H. Abed,et al.  CMOS VLSI Implementation of a Low-Power Logarithmic Converter , 2003, IEEE Trans. Computers.

[3]  Alex Pappachen James,et al.  An Artificial Cellular Convolution Architecture for Real-Time Image Processing , 2012 .

[4]  ERNEST L. HALL,et al.  Generation of Products and Quotients Using Approximate Binary Logarithms for Digital Filtering Applications , 1970, IEEE Transactions on Computers.

[5]  Celina M. H. de Figueiredo,et al.  Reversible Karatsuba's Algorithm , 2006, J. Univers. Comput. Sci..

[6]  Chip-Hong Chang,et al.  A Low Error and High Performance Multiplexer-Based Truncated Multiplier , 2010, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[7]  Gang Zhou,et al.  Complexity Analysis and Efficient Implementations of Bit Parallel Finite Field Multipliers Based on Karatsuba-Ofman Algorithm on FPGAs , 2010, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[8]  Akashi Satoh,et al.  Systematic Design of RSA Processors Based on High-Radix Montgomery Multipliers , 2011, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[9]  Khalid H. Abed,et al.  VLSI Implementation of a Low-Power Antilogarithmic Converter , 2003, IEEE Trans. Computers.

[10]  Davide De Caro,et al.  Efficient Logarithmic Converters for Digital Signal Processing Applications , 2011, IEEE Transactions on Circuits and Systems II: Express Briefs.

[11]  Patricio Bulic,et al.  An iterative logarithmic multiplier , 2011, Microprocess. Microsystems.

[12]  Patricio Bulic,et al.  A simple pipelined logarithmic multiplier , 2010, 2010 IEEE International Conference on Computer Design.

[13]  Saeid Belkasim,et al.  Accelerated 2D Image Processing on GPUs , 2005, International Conference on Computational Science.

[14]  Muhammad H. Rais Efficient Hardware Realization of Truncated Multipliers using FPGA , 2009 .

[15]  Khan A. Wahid,et al.  Fast Algorithm of A 64-bit Decimal Logarithmic Converter , 2010, J. Comput..

[16]  D.J. Mclaren,et al.  Improved Mitchell-based logarithmic multiplier for low-power DSP applications , 2003, IEEE International [Systems-on-Chip] SOC Conference, 2003. Proceedings..

[17]  V. Mahalingam,et al.  Improving Accuracy in Mitchell's Logarithmic Multiplication Using Operand Decomposition , 2006, IEEE Transactions on Computers.

[18]  Rached Tourki,et al.  Efficient Large Numbers Karatsuba-Ofman Multiplier Designs for Embedded Systems , 2009 .