A texture image restoration model based on combined subdivision was proposed in this paper, which can solve the problems of piecewise iterative curve fitting, especially the discontinuous contour and the size error of reconstruction regions. Firstly, segmentation regions of the original image were extracted. The feature vector of region shape was got by using contour tracing and downsampling. Then the region contour curve was reconstructed by combining ternary approximating and interpolating subdivision scheme. Finally, region texture was synthesized to get texture image restoration result. The proposed model had been tested on many natural images. The experimental results show that the proposed model is valid and the restoration results are consistent with human visual system. The proposed algorithm has lower time complexity of image restoration, and its performance in subjective assessment of the quality of pictures is much better than the multi-region image reconstruction algorithm.

To achieve medium level visual region texture substitution in multi-regions contour curves, a multi-region image reconstruction algorithm was proposed. Firstly, the segmented region and index list of original image were extracted. Secondly, the polynomial coefficients representing region structure feature were got by piecewise iterative curve fitting and the smallest region texture sample was selected. Finally, the reconstructed region contour and synthesized region texture were used to achieve regional restoration. The proposed algorithm can be done successfully for images with massive textures. The experimental results show that it can reduce the amount of data required by image reconstruction and be applied to reconstruct the still background of image and video.