Multiframe resolution-enhancement methods for compressed video

GÜNTÜRK B. K., Altunbasak Y., Mersereau R.

IEEE Signal Processing Letters, cilt.9, sa.6, ss.170-174, 2002 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 9 Sayı: 6
  • Basım Tarihi: 2002
  • Doi Numarası: 10.1109/lsp.2002.800503
  • Dergi Adı: IEEE Signal Processing Letters
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.170-174
  • Anahtar Kelimeler: high-resolution video, maximum a posteriori probability (MAP), Motion Pictures Experts Group (MPEG), multiframe restoration, projections onto convex sets (POCS), resolution enhancement, superresolution (SR), video quality
  • İstanbul Medipol Üniversitesi Adresli: Evet

Özet

Multiframe resolution enhancement ("superresolution") methods are becoming widely studied, but only a few procedures have been developed to work with compressed video, despite the fact that compression is a standard component of most image- and video-processing applications. One of these methods uses quantization-bound information to define convex sets and then employs a technique called "projections onto convex sets" (POCS) to estimate the original image. Another uses a discrete cosine transformation (DCT)-domain Bayesian estimator to enhance resolution in the presence of both quantization and additive noise. The latter approach is also capable of incorporating known source statistics and other reconstruction constraints to impose blocking artifact reduction and edge enhancement as part of the solution. In this article we propose a spatial-domain Bayesian estimator that has advantages over both of these approaches.