Speckle images denoising in laser projection displaying

In the paper, we achieved the speckle image statistics restoration by computing the most likely state at each pixel based on hidden Markov models (HMM). Among the features of the proposed method, HMM takes the adaptive window size which allows us to obtain a better estimate of the local variance of...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Wang Junli, Song Zhengxun, Yin Fuchang
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:In the paper, we achieved the speckle image statistics restoration by computing the most likely state at each pixel based on hidden Markov models (HMM). Among the features of the proposed method, HMM takes the adaptive window size which allows us to obtain a better estimate of the local variance of the noise for different regions of the image. Therefore, the additive noise is removed more in the smooth regions while the edges are preserved in nonsmooth ones. Another feature of this method has to do with the proportionality of the execution time and the noise power. Meanwhile, the software and hardware of speckle measurement system are designed and realized in laser projection displaying based on LabVIEW flat. The performance of this soft algorithm indicated that the restored images have higher contrast and clearness which is attributed to nearly optimal usage of the statistical properties of the image by HMM.
DOI:10.1109/URKE.2011.6007897