Movie denoising by average of warped lines

Marcelo Bertalmío, Vicent Caselles, Álvaro Pardo

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Here, we present an efficient method for movie denoising that does not require any motion estimation. The method is based on the well-known fact that averaging several realizations of a random variable reduces the variance. For each pixel to be denoised, we look for close similar samples along the level surface passing through it. With these similar samples, we estimate the denoised pixel. The method to find close similar samples is done via warping lines in spatiotemporal neighborhoods. For that end, we present an algorithm based on a method for epipolar line matching in stereo pairs which has per-line complexity O(N), where N is the number of columns in the image. In this way, when applied to the image sequence, our algorithm is computationally efficient, having a complexity of the order of the total number of pixels. Furthermore, we show that the presented method is unsupervised and is adapted to denoise image sequences with an additive white noise while respecting the visual details on the movie frames. We have also experimented with other types of noise with satisfactory results.

Original languageEnglish
Pages (from-to)2333-2347
Number of pages15
JournalIEEE Transactions on Image Processing
Volume16
Issue number9
DOIs
StatePublished - Sep 2007

Keywords

  • Denoising
  • Image sequence restoration
  • Movie denoising
  • Unsupervised filtering
  • Warping

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