Region-of-interest tomography using multiresolution interpolation

The wavelet localization technique has been applied to region-of-interest tomography. It achieves a significant saving in the required projections if only a small region of a tomographic image is of interest. We first 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 simpler 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 32×32 pixels region of a 256×256 pixels image. The signal-to-error ratio of the reconstructed region-of-interest is over 50 dB as compare with the case of full projection. Moreover, we also investigate the effect 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