Corrections to ‘Area- and Power-Efficient Design of Daubechies Wavelet Transforms Using Folded AIQ Mapping’

Abstract

Islam and Wahid proposed an area-and powerefficient design of Daubechies wavelet transforms. However, it was found that the matrix decompositions of the folded algebraicinteger-quantization scheme for DAUB4 and DAUB6 are incorrect and do not correspond with their architecture designs. We propose modifications not only to the algorithm but also to its implementation. Compared with the original method, the proposed design requires fewer adders and maintains the same critical path.Index Terms-Algebraic integer quantization (AIQ), Daubechies wavelet, error-free algorithm, folded mapping.

Memory-efficient Very Large Scale Integration Architecture of 2D Algebraic-integer-based Daubechies Discrete Wavelet Transform

“…(15) In addition, the very large scale integration (VLSI) architecture does not use multipliers except in the final reorganization stage, which can increase its speed and reduce the area used by hardware. (10,12,(15)(16)(17)(18)(19)(20)(21)(22) The Daubechies wavelet transform can be used to compress sensing data by employing a sparsifying linear transformation for different imaging systems, including those for optical imaging, radio astronomy, computed tomography, and magnetic resonance imaging. (21) Casson investigated an analog domain signal processing circuit, which was used to approximate the output of the DWT architecture used in combination with ultralow-power wearable sensors.…”