A new Landweber algorithm for 3D microscopy deconvolution is introduced in this paper. The algorithm is formulated from the Fredholm equation of the first kind. Artificial 3D images are used to test this algorithm and the restored results are compared with a nonlinear iterative de-convolution algorithm (IDA). The experimental results show that the Landweber algorithm can effectively suppress background noise and remove asymmetric point spread function (PSF) degradation. Finally, a typical real 3D confocal image is restored by the Landweber algorithm and the results are compared with IDA.
|Number of pages||4|
|Publication status||Published - 2004|
|Event||17th International Conference on Pattern Recognition - Cambridge, United Kingdom|
Duration: 23 Aug 2004 → 26 Aug 2004
|Conference||17th International Conference on Pattern Recognition|
|Period||23/08/04 → 26/08/04|