Wavelet-denoising on hardware devices with Perfect Reconstruction, low latency and adaptive thresholding

• Published in: Computers & electrical engineering 2013-05, Vol.39 (4), p.1300-1311
• Main Authors: Ballesteros L, Dora M., Moreno A, Juan M.
• Format: Article
• Language: English
• Subjects: Architecture; Architecture (computers); Computer simulation; Delay; Enginyeria electrònica; Hardware; Matemàtiques i estadística; Ondetes (Matemàtica); Permissible error; Quantization; Reconstruction; Wavelet; Wavelets (Mathematics); Àrees temàtiques de la UPC
• ISSN: 0045-7906; 1879-0755
• DOI: 10.1016/j.compeleceng.2013.03.005

•We introduce a wavelet adaptive-denoising architecture for real-time 1D-systems.•The Perfect Reconstruction of the wavelet transform is satisfied.•It includes five blocks: dwt, idwt, median, thresholding and delay.•The adaptive threshold is based on a real-time sorting process.•The quantization error, delay and latency are better than in related works. This paper introduces a wavelet denoising architecture with adaptive thresholding for real-time 1D-systems and without the use of external memories for storing input data or wavelet coefficients. The Discrete Wavelet Transform (DWT) is executed sample-by-sample by a polyphase scheme of the biorthogonal base 5/3. Since the weights of the filters are represented by integer terms and the quantization error is quasi-zero, the principle of Perfect Reconstruction is satisfied. The adaptive threshold is based on a real-time sorting process which calculates the median of the detail coefficients. Simulations are presented to measure the delay, latency, quantization error and hardware cost. A comparison with related works is also provided in order to show the strengths of the current proposal. The good trade-off among reconstruction error, latency, delay and hardware cost permits to use the proposed architecture in a wide variety of signals that require good fidelity and prompt response.