Abstract

The maximum entropy algorithm MENT is extended to image reconstruction problems frequently encountered in industrial computerized tomography. Unlike MENT, the extended MENT algorithm can process prior information and deal with incomplete projections or limited angle data. The image processing performance of the extended MENT algorithm is better than that of other maximum entropy algorithms such as MART or more standard methods such as ART and convolution backprojection. It is shown that the extended MENT algorithm outperforms these algorithms when few projections are collected, when limited angle data are available, or when data are missing in the projections. >

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