Optimized nonorthogonal transforms for image compression

This paper proposes an algorithm for improving the performance of standard block transform coding algorithms by better exploiting the correlations between transform coefficients. While standard algorithms focus on decorrelating coefficients within each block, the new approach focuses on exploiting correlations between coefficients of different blocks. Interblock correlations are minimized by linearly estimating coefficients from previously transmitted neighboring block coefficients. The use of linear estimators between blocks leads to a nonorthogonal representation of the image. Quantization issues relating to this nonorthogonal transform are addressed, and an image coding implementation is simulated. Simulations demonstrate that large improvements are observed over standard block transform coding systems, over a wide range of bitrates.