A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image compression and transmission using wavelets and vector quantization
Image compression and transmission using wavelets and vector quantization
| Hi-index | 0.00 |
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