A Statistical Information Reconstruction Method of Images Based on Multiple-Point Geostatistics Integrating Soft Data with Hard Data

Abstract

The statistical information reconstruction of images will be difficult and inaccurate when no conditional data or only hard data are available. Accuracy of reconstructed images can be improved, using soft data during the process of reconstruction. Integrating soft data with hard data, a method based on multiple-point geostatistics is proposed to reconstruct statistical information of images. During the process of regenerating characteristic patterns in a training image, the accuracy of reconstructed images is improved, using both soft data and hard data as conditional data. The experimental results show that, compared with the unconditional reconstructed images and the reconstructed images using only hard data, the structure characteristics in reconstructed images using the proposed method are more similar to those obtained from real volume data.