Research Frontiers in Object Technology
Information Systems Frontiers
| Hi-index | 0.00 |
This paper proposes a two-stage global motion parameter estimation method using block-based motion vectors and a model failure (MF) object compensation algorithm by object-oriented fractal mapping of the residual image for an object-oriented coder. In the first stage of the two-stage motion parameter estimation algorithm, coarse motion parameters are estimated by fitting block-based motion vectors computed hierarchically to a six-parameter model, and in the second stage, the estimated motion parameters are refined by the gradient method using an image reconstructed by motion parameters detected in the first stage. The local prediction error by the six-parameter method is locally reduced by blockwise motion parameter correction using the residual image. Finally, the MF object is compensated by object-oriented fractal mapping of the previous residual image into the current one, in which geometric affine mapping is followed by the massic transformation. For MF object compensation, the selection between motion parameter compensation and fractal mapping is achieved by the validity test. Computer simulation results show that the proposed method gives better performance than the conventional ones in terms of the peak signal-to-noise ratio (PSNR) and compression ratio (CR)