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Parallel Hardware-Software Architecture for computation of Discrete Wavelet Transform using the Recursive Merge Filtering algorithm
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Parallel Hardware-Software Architecture for computation of Discrete Wavelet Transform using the Recursive Merge Filtering
algorithm
Piyush Jamkhandi5 , Amar Mukherjee5 , Kunal Mukherjee5 and Robert Franceschini5 
| (5) |
School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, Florida, USA |
Abstract
We present an FPGA -based parallel hardware-software architecture for the computation of the Discrete Wavelet Transform (DWT),
using the Recursive Merge Filtering (RMF) algorithm. The DWT is built in a bottom-up fashion in logN steps, successively building
complete DWTs by “merging” two smaller DWTs and applying the wavelet filter to only the “smooth” or DC coefficient from the
smaller DWTs. The main bottleneck of this algorithm is the data routing process, which can be reduced by separating the computations
into two types to introduce parallelism. This is achieved by using a virtual mapping structure to map the input. The data
routing bottleneck has been transformed into simple arithmetic computations on the mapping structure. Due to the use of the
FPGA -RAM for the mapping structure, the total number of data accesses to the main memory are reduced. This architecture shows
how data routing in this problem can be transformed into a series of index computations
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