A spatially coherent discrete wavelet transform - accessing the localization property for data compression

Summary form only given. Wavelets intrinsically give us the capability of localized signal decomposition and analysis in space and frequency. We present the recursive merge filter (RMF) discrete wavelet transform (DWT) algorithm, that organizes intermediate coefficients with respect to both space and frequency. This allows close coupling and pipelining with the encoder, fine grained coding, and "cheap growing" of larger DWT from smaller ones in a constant number of filter operations. The RMF algorithm computes the DWT of an array of length N in a bottom-up fashion, by successively "merging" two smaller DWT (four in 2D), and applying the wavelet filter only on the "smooth" or DC coefficients.