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A coded imaging and decoding (image reconstruction) scheme was developed for diagnosing a hot and dense region emitting hard x-rays and neutrons in laser-fusion plasmas. Because the imager was a uniformly redundant array of penumbral aperture (URPA) arranged in an M-matrix, URPA leads to N times (N: the total number of apertures) enhancement of signal intensity in comparison with a single penumbral aperture. A recorded penumbral image was reconstructed by a computer-based heuristic method to reduce artifacts caused by noises contained in a penumbral image. Applicability of this technique was investigated by imaging x-rays emitted from laser-produced plasmas, demonstrating a spatial resolution of 16 microm. Under the present conditions, the spatial resolution was determined dominantly by a detector resolution (10.5 microm) and a signal-to-noise ratio of the obtained penumbral image.

Penumbral imaging technique can be applied to highly penetrating radiations such that of as neutrons. In penumbral imaging, the source image can be recovered from its penumbral image by deconvolution. The method is an efficient imaging technique for fast ignition research. However, the γ rays produced by the fast-heating laser pollute the penumbral image as noise. Conventional deconvolution methods like the Wiener filter cannot obtain a clear reconstructed image from noisy penumbral image. In this paper, we propose a new reconstruction method by principal component analysis (PCA). The method can efficiently remove the noise by "training" images obtained from other experiments. We used the (2D) 2 PCA method as a noise reduction method, which is one of the PCA methods. The efficacy of the proposed method is demonstrated by computer simulation.

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