Image restoration method with multiframe projection filter
Manabu Kikuchi, Miki Haseyama, Hideo Kitajima · Systems and Computers in Japan · 1997
In this paper, we propose a multiframe projection filter (MFPF) that restores images using several observed images rather than one observed image by enhancing a conventional projection filter. By superimposing several observed images during image restoration, the MFPF reduces random noise. Use of the MFPF enables high-quality image restoration when several observed images of a specified object are available. Since image selection is crucial to the process of superimposition, we also propose a selection equation. The MFPF differs from the multiframe Wiener filter (MFWF), which also uses several observed images, in that it does not require original image correlation numbers during image restoration. Because the MFPF does not require such numbers, the MFPF offers superior image restoration in cases where the original image cannot be elucidated from observed images. At the end of this paper, we present summary findings from an image restoration experiment carried out using the proposed filter. But first, we will confirm the MFPF's effectiveness in superimposing images and give an example of a situation where, given the absence of an original image, the MFPF provides better image resolution than the MFWF. Finally, combining a method for estimating background noise dispersion and an equation for selecting which images to use for superimposition results in an image restoration system capable of functioning when random noise dispersion is unknown. Following the above scheme will confirm the effectiveness of our approach. © 1997 Scripta Technica, Inc. Syst Comp Jpn, 28(7): 65–75, 1997