Keywords: 
• 图像重建 /
• 闪光照相 /
• 广义变分 /
• 约束优化

Abstract: Blurring and noise are serious problems in hydro-test with high-energy X-ray radiography and make it difficult to reconstruct density distributions from radiographic images.A constrained optimization reconstruction method to decrease the blurring and noise impact is proposed.In this method,the parallel-beam X-ray projections are modeled by inserting a blurring ma-trix in.The optimization reconstruction problem is minimized by steepest descent method,and a preconditioned matrix has been adopted to improve the reconstruction efficiency.We focus on the tomographic reconstruction of piecewise smooth objects invol-ving sharp edges,so the algorithm is based on generalized-variation-minimization constraints,piecewise constraints and the non-negative density values constraints.We applied the reconstruction algorithm to reconstruct computer-synthesized images of the French Test Object (FTO)and a hydro-test object image.The results show that our method is beneficial to improve the quality of reconstructed image with better performance of noise smoothing and better edge preserving as well.