A survey of architectures for the discrete and continuous wavelet transforms

Wavelet transforms have proven to be useful tools for several applications, including signal analysis, signal coding, and image compression. This paper surveys the VLSI architectures that have been proposed for computing the discrete and continuous wavelet transforms for 1-D and 2-D signals. The proposed architectures range from SIMD arrays to folded architectures such as systolic arrays and parallel filters. The SIMD arrays have a size that is proportional to that of the data sequence and are optimal with respect to time. The folded architectures, on the other hand, support single chip implementations and are optimal with respect to both area and time under the word-serial model.