Holographic imaging modalities are gaining increasing interest in various application domains ranging from microscopy to high-end autostereoscopic displays. While much effort has been spent on the development of the optics, photonics and micro/nano-electronics that enable the design of holographic capturing and visualization devices, relatively few research effort has been targeted towards the underlying signal processing. One significant challenge relates to the fact that the data volumes needed in support of this kind of holographic applications is rapidly increasing: for visualization devices, and in particular holographic displays, unprecedented resolutions are desired resulting in huge bandwidth requirements on both the communication channels and internal computing and data channels. An additional challenge relates to the fact that we are handling an interference-based modality being complex amplitude based in nature. Both challenges lead to the fact that for example classic data representations and coding solutions fail to handle holographic data in an effective way. This paper attempts to provide some insights that enable to alleviate or a least reduce these bottlenecks and sketch an avenue for the development of efficient source coding solutions. Moreover, it will also outline the efforts the JPEG committee is undertaking in the context of the JPEG Pleno standardization programme to roll out a path for data interoperability of holographic solutions.
Holograms, either optically acquired or simulated numerically from 3D datasets, such as point clouds, have
special rendering requirements for display. Evaluating the quality of hologram generation techniques is not
straightforward, since high-quality holographic display technologies are still immature, In this paper we present
a framework for three-dimensional rendering of colour computer-generated holograms (CGHs) acquired from
point-clouds, on high-end light field displays. This allows for the rendering of holographic content with horizontal
parallax and wide viewing angle. We deploy prior work, namely a fast CGH method that inherently handles
occlusion problems to acquire high quality colour holograms from point clouds. Our experiments showed that
rendering holograms with the proposed framework provides 3D effect with depth disparity and horizontal-only
with wide viewing angle. Therefore, it allows for the evaluation of CGH techniques regarding functional properties
such as depth cues and efficient occlusion handling.
signal processing methods from software-driven computer engineering and applied mathematics. The compressed
sensing theory in particular established a practical framework for reconstructing the scene content using few linear
combinations of complex measurements and a sparse prior for regularizing the solution. Compressed sensing found
direct applications in digital holography for microscopy. Indeed, the wave propagation phenomenon in free space
mixes in a natural way the spatial distribution of point sources from the 3-dimensional scene. As the 3-dimensional
scene is mapped to a 2-dimensional hologram, the hologram samples form a compressed representation of the
scene as well. This overview paper discusses contributions in the field of compressed digital holography at the
micro scale. Then, an outreach on future extensions towards the real-size macro scale is discussed. Thanks to
advances in sensor technologies, increasing computing power and the recent improvements in sparse digital signal
processing, holographic modalities are on the verge of practical high-quality visualization at a macroscopic scale
where much higher resolution holograms must be acquired and processed on the computer.
Digital holography is mainly used today for metrology and microscopic imaging and is emerging as an important potential technology for future holographic television. To generate the holographic content, computer-generated holography (CGH) techniques convert geometric descriptions of a 3D scene content. To model different surface types, an accurate model of light propagation has to be considered, including for example, specular and diffuse reflection. In previous work, we proposed a fast CGH method for point cloud data using multiple wavefront recording planes, look-up tables (LUTs) and occlusion processing. This work extends our method to account for diffuse reflections, enabling rendering of deep 3D scenes in high resolution with wide viewing angle support. This is achieved by modifying the spectral response of the light propagation kernels contained by the look-up tables. However, holograms encoding diffuse reflective surfaces depict significant amounts of speckle noise, a problem inherent to holography. Hence, techniques to improve the reduce speckle noise are evaluated in this paper. Moreover, we propose as well a technique to suppress the aperture diffraction during numerical, viewdependent rendering by apodizing the hologram. Results are compared visually and in terms of their respective computational efficiency. The experiments show that by modelling diffuse reflection in the LUTs, a more realistic yet computationally efficient framework for generating high-resolution CGH is achieved.
Recently several papers reported efficient techniques to compress digital holograms. Typically, the rate-distortion performance of these solutions was evaluated by means of objective metrics such as Peak Signal-to-Noise Ratio (PSNR) or the Structural Similarity Index Measure (SSIM) by either evaluating the quality of the decoded hologram or the reconstructed compressed hologram. Seen the specific nature of holograms, it is relevant to question to what extend these metrics provide information on the effective visual quality of the reconstructed hologram. Given that today no holographic display technology is available that would allow for a proper subjective evaluation experiment, we propose in this paper a methodology that is based on assessing the quality of a reconstructed compressed hologram on a regular 2D display. In parallel, we also evaluate several coding engines, namely JPEG configured with the default perceptual quantization tables and with uniform quantization tables, JPEG 2000, JPEG 2000 extended with arbitrary packet decompositions and direction-adaptive filters and H.265/HEVC configured in intra-frame mode. The experimental results indicate that the perceived visual quality and the objective measures are well correlated. Moreover, also the superiority of the HEVC and the extended JPEG 2000 coding engines was confirmed, particularly at lower bitrates.
With the advent of modern computing and imaging technologies, digital holography is becoming widespread in various scientific disciplines such as microscopy, interferometry, surface shape measurements, vibration analysis, data encoding, and certification. Therefore, designing an efficient data representation technology is of particular importance. Off-axis holograms have very different signal properties with respect to regular imagery, because they represent a recorded interference pattern with its energy biased toward the high-frequency bands. This causes traditional images’ coders, which assume an underlying 1/f2 power spectral density distribution, to perform suboptimally for this type of imagery. We propose a JPEG 2000-based codec framework that provides a generic architecture suitable for the compression of many types of off-axis holograms. This framework has a JPEG 2000 codec at its core, extended with (1) fully arbitrary wavelet decomposition styles and (2) directional wavelet transforms. Using this codec, we report significant improvements in coding performance for off-axis holography relative to the conventional JPEG 2000 standard, with Bjøntegaard delta-peak signal-to-noise ratio improvements ranging from 1.3 to 11.6 dB for lossy compression in the 0.125 to 2.00 bpp range and bit-rate reductions of up to 1.6 bpp for lossless compression.
With the advent of modern computing and imaging technologies, the use of digital holography became practical in many applications such as microscopy, interferometry, non-destructive testing, data encoding, and certification. In this respect the need for an efficient representation technology becomes imminent. However, microscopic holographic off-axis recordings have characteristics that differ significantly from that of regular natural imagery, because they represent a recorded interference pattern that mainly manifests itself in the high-frequency bands. Since regular image compression schemes are typically based on a Laplace frequency distribution, they are unable to optimally represent such holographic data. However, unlike most image codecs, the JPEG 2000 standard can be modified to efficiently cope with images containing such alternative frequency distributions by applying the arbitrary wavelet decomposition of Part 2. As such, employing packet decompositions already significantly improves the compression performance for off-axis holographic images over that of regular image compression schemes. Moreover, extending JPEG 2000 with directional wavelet transforms shows even higher compression efficiency improvements. Such an extension to the standard would only require signaling the applied directions, and would not impact any other existing functionality. In this paper, we show that wavelet packet decomposition combined with directional wavelet transforms provides efficient lossy-to-lossless compression of microscopic off-axis holographic imagery.
Publisher’s Note: This paper, originally published on 9/26/2013, was replaced with a corrected/revised version on
7/9/2014. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital
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Significant research efforts have been invested in attempting to reliably capture and visualize holograms since their
inception in 1962. However, less attention has been given to the efficient digital representation of the recorded
holograms, which differ considerably from digitally recorded photographs. This paper examines the properties of
recorded off-axis holograms and attempts to find a suitable sparse representation for holographic data. Results show
significantly improved Bjøntegaard delta PSNR of over 4.5 dB on average within a bit-rate range of 0.125 to 2 bpp when
combining the direction-adaptive discrete wavelet transform with non-standard decomposition schemes for off-axis
holographic recordings; up to 7.5% reduction of file size has been achieved in the lossless case.