Gradient-based Space Filling Curves: Application to lossless image compression

Most conventional lossless image compression schemes such as GIF and PNG use entropic coding to reduce redundancies that results in adjacent pixels correlation. In such schemes, images are scanned line by line, and so, only horizontal patterns are effectively compressed. The proposed approach attempts to more explore image correlation in different direction by adopting a context based scanning process. An image is scanned along a space filling curve (SFC) so as to exploit inherent coherence in the image. The used SFC is determined by a gradient based method allowing the detection pixel´s change direction. The resulting one-dimensional representation of the image should have improved auto-correlation compared with universal scans. Combined with conventional lossless image compression techniques such as GIF and PNG, the proposed scan shows significant compression efficiency improvement. The new algorithm used for SFC determination is presented and it is used as an input to conventional coding scheme.