Roadmap on computational methods in optical imaging and holography [invited].

Unlabelled: Computational methods have been established as cornerstones in optical imaging and holography in recent years. Every year, the dependence of optical imaging and holography on computational methods is increasing significantly to the extent that optical methods and components are being completely and efficiently replaced with computational methods at low cost. This roadmap reviews the current scenario in four major areas namely incoherent digital holography, quantitative phase imaging, imaging through scattering layers, and super-resolution imaging.

Autoregressive modeling for lossless compression of holograms.

The large number of pixels to be processed and stored for digital holographic techniques necessitates the development of effective lossless compression techniques. Use cases for such techniques are archiving holograms, especially sensitive biomedical data, and improving the data transmission capacity of bandwidth-limited data transport channels where quality loss cannot be tolerated, like display interfaces. Only a few lossless compression techniques exist for holography, and the search for an efficient technique well suited for processing the large amounts of pixels typically encountered is ongoing.

Deep hologram converter from low-precision to middle-precision holograms.

We propose a deep hologram converter based on deep learning to convert low-precision holograms into middle-precision holograms. The low-precision holograms were calculated using a shorter bit width. It can increase the amount of data packing for single instruction/multiple data in the software approach and the number of calculation circuits in the hardware approach.

JPEG Pleno holography presents the numerical reconstruction software for holograms: an excursion in holographic views.

Digital reconstructions of numerical holograms enable data visualization and serve a multitude of purposes ranging from microscopy to holographic displays. Over the years, many pipelines have been developed for specific hologram types. Within the standardization effort of JPEG Pleno holography, an open-source MATLAB toolbox was developed that reflects the best current consensus.

Three-dimensional spline-based computer-generated holography.

Electro-holography is a promising 3D display technology, as it can, in principle, account for all visual cues. Computing the interference patterns to drive them is highly calculation-intensive, requiring the design and development of efficient computer-generated holography (CGH) algorithms to facilitate real-time display. In this work, we propose a new algorithm for computing the CGH for arbitrary 3D curves using splines, as opposed to previous solutions, which could only draw planar curves.

Binary hologram compression using context based Bayesian tree models with adaptive spatial segmentation.

With holographic displays requiring giga- or terapixel resolutions, data compression is of utmost importance in making holography a viable technique in the near future. In addition, since the first-generation of holographic displays is expected to require binary holograms, associated compression algorithms are expected to be able to handle this binary format. In this work, the suitability of a context based Bayesian tree model is proposed as an extension to adaptive binary arithmetic coding to facilitate the efficient lossless compression of binary holograms.

Variable-intensity line 3D images drawn using kinoform-type electroholography superimposed with phase error.

Three-dimensional (3D) display using electroholography is a promising technology for next-generation television systems; however, its applicability is limited by the heavy computational load for obtaining computer-generated holograms (CGHs). The CG-line method is an algorithm that calculates CGHs to display 3D line-drawn objects at a very high computational speed but with limited expressiveness; for instance, the intensity along the line must be constant. Herein, we propose an extension for drawing gradated 3D lines using the CG-line method by superimposing phase noise.

Miniaturized cost-effective broadband spectrometer employing a deconvolution reconstruction algorithm for resolution enhancement.

We demonstrate a miniaturized broadband spectrometer employing a reconstruction algorithm for resolution enhancement. We use an opto-digital co-design approach, by firstly designing an optical system with certain residual aberrations and then correcting these aberrations with a digital algorithm. The proposed optical design provides an optical resolution less than 1.

Pincushion point-spread function for computer-generated holography.

Point-spread functions (PSFs) are non-stationary signals whose spatial frequency increases with the radius. These signals are only meaningful over a small spatial region when being propagated over short distances and sampled with regular sampling pitch. Otherwise, aliasing at steep incidence angles leads to the computation of spurious frequencies.

Off-axis image plane hologram compression in holographic tomography - metrological assessment.

In this paper, we present a novel study on the impact of lossy data compression on the metrological properties of holographic tomography reconstruction of the refractive index (RI). We use a spatial bandwidth-optimized compression procedure that leverages the properties of image plane off-axis holograms and standardized compression codecs, both widely applied in research and industry. The compression procedure is tested at multiple bitrates, for four different objects and against three reconstruction algorithms.

Real-Time Computation of 3D Wireframes in Computer-Generated Holography.

Computer-Generated Holography (CGH) algorithms simulate numerical diffraction, being applied in particular for holographic display technology. Due to the wave-based nature of diffraction, CGH is highly computationally intensive, making it especially challenging for driving high-resolution displays in real-time. To this end, we propose a technique for efficiently calculating holograms of 3D line segments.

GPU-accelerated calculation of computer-generated holograms for line-drawn objects.

The heavy computational burden of computer-generated holograms (CGHs) has been a significant issue for three-dimensional (3D) display systems using electro-holography. Recently, fast CGH calculation methods of line-drawn objects for electro-holography were proposed, which are targeted for holography-based augmented reality/virtual reality devices because of their ability to project object contours in space with a small computational load. However, these methods still face shortcomings, namely, they cannot draw arbitrary curves with graphics processing unit (GPU) acceleration, which is an obstacle for replaying highly expressive and complex 3D images.

Photorealistic computer generated holography with global illumination and path tracing.

Computer generated holography (CGH) algorithms come in many forms, with different trade-offs in terms of visual quality and calculation speed. However, no CGH algorithm to date can accurately account for all 3D visual cues simultaneously, such as occlusion, shadows, continuous parallax, and precise focal cues, without view discretization. The aim is to create photorealistic CGH content, not only for display purposes but also to create reference data for comparing and testing CGH and compression algorithms.

JPEG Pleno holography: scope and technology validation procedures.

JPEG Pleno is a standardization framework addressing the compression and signaling of plenoptic modalities. While the standardization of solutions to handle light field content is currently reaching its final stage, the Joint Photographic Experts Group (JPEG) committee is now preparing for the standardization of solutions targeting point cloud and holographic modalities. This paper addresses the challenges related to the standardization of compression technologies for holographic content and associated test methodologies.

Suitability analysis of holographic vs light field and 2D displays for subjective quality assessment of Fourier holograms.

Measuring the impact of compression on the reconstruction quality of holograms remains a challenge. A public subjectively-annotated holographic data set that allows for testing the performance of compression techniques and quality metrics is presented, in addition to a subjective visual quality assessment methodology. Moreover, the performance of the quality assessment procedures is compared for holographic, regular 2D and light field displays.

Analytic computation of line-drawn objects in computer generated holography.

Digital holography is a promising display technology that can account for all human visual cues, with many potential applications i.a. in AR and VR.

Spatial bandwidth-optimized compression of image plane off-axis holograms with image and video codecs.

Image plane off-axis holograms (IP-OAH) are the most common data captured in digital holographic microscopy and tomography. Due to increasing storage and data transmission requirements, lossy compression of such holograms has been subject of earlier investigations. However, hologram compression can not be allowed to hinder the metrological capabilities of the measurement technique itself.

Dedicated processor for hologram calculation using sparse Fourier bases.

Recently, a calculation method involving sparse point spread functions in the short-time Fourier transform (STFT) domain was proposed. In this paper, a dedicated processor using the STFT algorithm is described, which is implemented on a field-programmable gate array. All the operations in this algorithm are implemented using fixed-point arithmetic.

Phase added sub-stereograms for accelerating computer generated holography.

Phase-added stereograms are a form of sparse computer generated holograms, subdividing the hologram in small Fourier transformed blocks and updating a single coefficient per block and per point-spread function. Unfortunately, these algorithms' computational performance is often bottlenecked by the relatively high memory requirements. We propose a technique to partition the 3D point cloud into cells using time-frequency analysis, grouping the affected coefficients into subsets that improve caching and minimize memory requirements.

Object-based digital hologram segmentation and motion compensation.

Digital video holography faces two main problems: 1) computer-generation of holograms is computationally very costly, even more when dynamic content is considered; 2) the transmission of many high-resolution holograms requires large bandwidths. Motion compensation algorithms leverage temporal redundancies and can be used to address both issues by predicting future frames from preceding ones. Unfortunately, existing holographic motion compensation methods can only model uniform motions of entire 3D scenes.

Efficient holographic video generation based on rotational transformation of wavefields.

High-quality holographic video generation requires both high computational resources and time; therefore, algorithms that can generate holographic videos efficiently will be soon in demand for dynamic holographic 3D displays. In this work, we present two algorithms that use a motion compensation scheme - based on the rotational transformation of wavefields [Appl. Opt.

Exact global motion compensation for holographic video compression.

Holographic video requires impractical bitrates for storage and transmission without data compression. We introduce an end-to-end compression pipeline for compressing holographic sequences with known ground truth motion. The compression strategy employs a motion compensation algorithm based on the rotational transformation of an angular spectrum.

Wave atoms for digital hologram compression.

Compression of macroscopic digital holograms is a major research problem, which if unresolved will continue to limit the possible applications of holography in multimedia contexts. The quest of searching for the most suitable representation for compression is still an open problem. In this work, we study sparsification by the wave atom transform, introduced in 2006 by Demanet et al.

Dynamic-range compression scheme for digital hologram using a deep neural network.

This Letter aims to propose a dynamic-range compression and decompression scheme for digital holograms that uses a deep neural network (DNN). The proposed scheme uses simple thresholding to compress the dynamic range of holograms with 8-bit gradation to binary holograms. Although this can decrease the amount of data by one-eighth, the binarization strongly degrades the image quality of the reconstructed images.

Impact of JPEG 2000 compression on deep convolutional neural networks for metastatic cancer detection in histopathological images.

The availability of massive amounts of data in histopathological whole-slide images (WSIs) has enabled the application of deep learning models and especially convolutional neural networks (CNNs), which have shown a high potential for improvement in cancer diagnosis. However, storage and transmission of large amounts of data such as gigapixel histopathological WSIs are challenging. Exploiting lossy compression algorithms for medical images is controversial but, as long as the clinical diagnosis is not affected, is acceptable.