Region-of-interest tomography using multiresolution interpolation

The wavelet localization technique was recently applied to the application of Region-of-Interest tomography. It achieves a signi cant saving in the required projections if only a small region of a tomographic image is of interest. In this paper, we rstly show that, with the same sampling requirement, a simple interpolation scheme applied on the samples can give a result at least as good as that achieved by using the wavelet localization approach. It means that we can use a much simple approach to achieve the same performance. Second, we propose a new sampling scheme such that the required projections of each angle are further reduced in a multiresolution form. With this sampling scheme, more than 84% of projections are saved to reconstruct a 32x32 pixels region of a 256x256 pixels image. The signal-to-error ratio of the reconstructed region-of-interest is over 50dB as compare with the case of full projection. Moreover, we also investigate the e ect of applying the interlaced sampling scheme on the proposed method. It is seen that a further reduction in the sampling requirement can be achieved although a slight decrease in signal-to-error ratio may result.