Accelerating SVD on reconfigurable hardware for image denoising

This paper presents the implementation on FPGA of a block SVD method for image denoising. This method exploits the fact that only the smallest singular values are affected by the noise and therefore can be discarded, leading to an efficient nonlinear image filtering. An efficient architecture for singular value decomposition, (SVD) based on the Brent, Luk, Van loan (BLV) systolic array, has been proposed. The architecture is three times more efficient and three times faster than the existing BLV structure. An optimised implementation has been efficiently carried out on the PP-RC1000 board using a high level language "Handel-C" for hardware design.

[1]  Jack E. Volder,et al.  The CORDIC computing technique , 1899, IRE-AIEE-ACM '59 (Western).

[2]  H. Andrews,et al.  Singular value decompositions and digital image processing , 1976 .

[3]  Joseph R. Cavallaro,et al.  CORDIC arithmetic for an SVD processor , 1987, IEEE Symposium on Computer Arithmetic.

[4]  R. Brent,et al.  The Solution of Singular-Value and Symmetric Eigenvalue Problems on Multiprocessor Arrays , 1985 .

[5]  Jack E. Volder The CORDIC Trigonometric Computing Technique , 1959, IRE Trans. Electron. Comput..

[6]  J. F. Böhme,et al.  Reducing the computations of the singular value decomposition array given by Brent and Luk , 1991 .

[7]  Abbes Amira,et al.  Improved SVD systolic array and implementation on FPGA , 2003, Proceedings. 2003 IEEE International Conference on Field-Programmable Technology (FPT) (IEEE Cat. No.03EX798).