Digital Holography Data Compression

Digital holography processing is a research topic related to the development of novel visual immersive applications. The huge amount of information conveyed by a digital hologram and the different properties of holographic data with respect to conventional photographic data require a comprehension of the performances and limitations of current image and video standard techniques. This paper proposes an architecture for objective evaluation of the performances of the state-of-the-art compression techniques applied to digital holographic data

Wavelet compression of digital holograms: Towards a view-dependent framework

International audienceAn analysis and discussion on the relevance of various wavelet schemes for hologram compression and reconstruction when the rendering configuration makes it possible to exploit selective refinements to perform a viewpoint-based degraded reconstruction. It is observed that Gabor wavelet bases have better time-frequency localization as compared to Fresnelet bases and hence are well suited for view-dependent compression techniques for hologram reconstruction

Cognitive Information Processing

Contains reports on seven research projects.National Institutes of Health (Grant 5 P01 GM14940-03)National Institutes of Health (Grant 5 P01 GM15006-02)Joint Services Electronics Programs (U. S. Army, U.S. Navy, and U.S. Air Force) under Contract DA 28-043-AMC-02536(E)National Institutes of Health (Grant 5 TOl GM-01555-02

Assessment of speckle denoising filters for digital holography using subjective and objective evaluation models

Digital holography is an emerging imaging technique for displaying and sensing three dimensional objects. The perceived image quality of a hologram is frequently corrupted by speckle noise due to coherent illumination. Although several speckle noise reduction methods have been developed so far, there are scarce quality assessment studies to address their performance and they typically focus solely on objective metrics. However, these metrics do not reflect the visual quality perceived by a human observer. In this work, the performance of four speckle reduction algorithms, namely the nonlocal means, the Lee, the Frost and the block matching 3D filters, with varying parameterizations, were subjectively evaluated. The results were ranked with respect to the perceived image quality to obtain the mean opinion scores using pairwise comparison. The correlation between the subjective results and twenty different no-reference objective quality metrics was evaluated. The experiment indicates that block matching 3D and Lee are the preferred filters, depending on hologram characteristics. The best performing objective metrics were identified for each filter.info:eu-repo/semantics/publishedVersio