The use of field-programmable gate arrays (FPGAs) for digital signal processing (DSP) has increased with the introduction of dedicated multipliers, which allow the implementation of complex algorithms. This architecture is especially effective for data-intensive applications with extremes in data throughput. Recent studies prove that the FPGAs offer better solutions for real-time multiresolution video processing than any available processor, DSP or general-purpose. FPGA design of critically sampled discrete wavelet transforms has been thoroughly studied in literature over recent years. Much less research was done towards FPGA design of overcomplete wavelet transforms and advanced wavelet-domain video processing algorithms. This paper describes the parallel implementation of an advanced wavelet-domain noise filtering algorithm, which uses a nondecimated wavelet transform and spatially adaptive Bayesian wavelet shrinkage. The implemented arithmetic is decentralized and distributed over two FPGAs. The standard composite television video stream is digitalized and used as a source for real-time video sequences. The results demonstrate the effectiveness of the developed scheme for real-time video processing.