Advantages of using a space filling curve for computing wavelet transforms of road traffic images

The properties of computing wavelet transforms of road traffic image data are discussed. It is proposed to incorporate Hilbert scan of image data and a wavelet transform factorised into lifting steps. Scanning an image, in space filling curve order, brings together pixels that are highly correlated. This is a desirable property, because the objects of interest - vehicles comprise a bounded set of regular patches on an image. Applying a 1-dimensional wavelet transform requires a smaller number of processing steps than a separable two-dimensional transform. Such a solution is suitable for on site microcontroler or FPGA implementation.