Further optimization of SeDDaRA blind image deconvolution algorithm and its DSP implementation
2011
Efficient algorithm for blind image deconvolution and its high-speed implementation is of great value in practice.
Further optimization of SeDDaRA is developed, from algorithm structure to numerical calculation methods. The main
optimization covers that, the structure's modularization for good implementation feasibility, reducing the data
computation and dependency of 2D-FFT/IFFT, and acceleration of power operation by segmented look-up table. Then
the Fast SeDDaRA is proposed and specialized for low complexity. As the final implementation, a hardware system of
image restoration is conducted by using the multi-DSP parallel processing. Experimental results show that, the
processing time and memory demand of Fast SeDDaRA decreases 50% at least; the data throughput of image restoration
system is over 7.8Msps. The optimization is proved efficient and feasible, and the Fast SeDDaRA is able to support the
real-time application.
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