Showing papers in "Journal of The Optical Society of America A-optics Image Science and Vision in 2023"
TL;DR: In this paper , the authors summarized the advances in spectral imaging and its relevance, starting with spectral images (SIs) and their relevance and concluding with the most relevant compressive spectral optical systems.
Abstract: Spectral imaging collects and processes information along spatial and spectral coordinates quantified in discrete voxels, which can be treated as a 3D spectral data cube. The spectral images (SIs) allow the identification of objects, crops, and materials in the scene through their spectral behavior. Since most spectral optical systems can only employ 1D or maximum 2D sensors, it is challenging to directly acquire 3D information from available commercial sensors. As an alternative, computational spectral imaging (CSI) has emerged as a sensing tool where 3D data can be obtained using 2D encoded projections. Then, a computational recovery process must be employed to retrieve the SI. CSI enables the development of snapshot optical systems that reduce acquisition time and provide low computational storage costs compared with conventional scanning systems. Recent advances in deep learning (DL) have allowed the design of data-driven CSI to improve the SI reconstruction or, even more, perform high-level tasks such as classification, unmixing, or anomaly detection directly from 2D encoded projections. This work summarizes the advances in CSI, starting with SI and its relevance and continuing with the most relevant compressive spectral optical systems. Then, CSI with DL will be introduced, as well as the recent advances in combining the physical optical design with computational DL algorithms to solve high-level tasks.
2 citations
TL;DR: In this article , a synthetic hyperspectral video database is introduced, which offers the possibility to leverage the evaluation of algorithms in diverse applications, such as cross-spectral image reconstruction and video coder.
Abstract: In this paper, a synthetic hyperspectral video database is introduced. Since it is impossible to record ground-truth hyperspectral videos, this database offers the possibility to leverage the evaluation of algorithms in diverse applications. For all scenes, depth maps are provided as well to yield the position of a pixel in all spatial dimensions as well as the reflectance in spectral dimension. Two novel algorithms for two different applications are proposed to prove the diversity of applications that can be addressed by this novel database. First, a cross-spectral image reconstruction algorithm is extended to exploit the temporal correlation between two consecutive frames. The evaluation using this hyperspectral database shows an increase in peak signal-to-noise ratio (PSNR) of up to 5.6 dB dependent on the scene. Second, a hyperspectral video coder is introduced, which extends an existing hyperspectral image coder by exploiting temporal correlation. The evaluation shows rate savings of up to 10% depending on the scene.
TL;DR: In this article , the authors compared the performance of individuals with X-linked color-vision deficiencies (CVDs) to normal trichromats on the illumination discrimination task (IDT) performed in an immersive setting with a real scene illuminated by spectrally tunable LED lamps.
Abstract: Color constancy is the perceptual stability of surface colors under temporal changes in the illumination spectrum. The illumination discrimination task (IDT) reveals worse discrimination for "bluer" illumination changes in normal-trichromatic observers (changes towards cooler color temperatures on the daylight chromaticity locus), indicating greater stability of scene colors or better color constancy, compared with illumination changes in other chromatic directions. Here, we compare the performance of individuals with X-linked color-vision deficiencies (CVDs) to normal trichromats on the IDT performed in an immersive setting with a real scene illuminated by spectrally tunable LED lamps. We determine discrimination thresholds for illumination changes relative to a reference illumination (D65) in four chromatic directions, roughly parallel and orthogonal to the daylight locus. We find, using both a standard CIELUV metric and a cone-contrast metric tailored to distinct CVD types, that discrimination thresholds for daylight changes do not differ between normal trichromats and CVD types, including dichromats and anomalous trichromats, but thresholds for atypical illuminations do differ. This result extends a previous report of illumination discrimination ability in dichromats for simulated daylight changes in images. In addition, using the cone-contrast metric to compare thresholds for bluer and yellower daylight changes with those for unnatural redder and greener changes, we suggest that reduced sensitivity to daylight changes is weakly preserved in X-linked CVDs.
TL;DR: In this paper , a model-based approach is presented to comprehensively model nonlinear optical microscopy in scattering media, including signal generation, radiation, and far-field detection.
Abstract: The development and application of nonlinear optical (NLO) microscopy methods in biomedical research has experienced rapid growth over the past three decades. Despite the compelling power of these methods, optical scattering limits their practical use in biological tissues. This tutorial offers a model-based approach illustrating how analytical methods from classical electromagnetism can be employed to comprehensively model NLO microscopy in scattering media. In Part I, we quantitatively model focused beam propagation in non-scattering and scattering media from the lens to focal volume. In Part II, we model signal generation, radiation, and far-field detection. Moreover, we detail modeling approaches for major optical microscopy modalities including classical fluorescence, multi-photon fluorescence, second harmonic generation, and coherent anti-Stokes Raman microscopy.
TL;DR: The present erratum is intended to correct some typos as well as to complement Appendices B and C in this paper , and it is also intended to complement the present paper [JOAOD60740-323210.36.000403].
Abstract: The present erratum is intended to correct some typos as well as to complement Appendices B and C in our paper [J. Opt. Soc. Am. A36, 403 (2019)JOAOD60740-323210.1364/JOSAA.36.000403].
TL;DR: In this article , a purely analytical extension of flattened Gaussian beams to any values of beam order is proposed, and the paraxial propagation problem of axially symmetric, coherent flat-top beams through arbitrary ABCD optical systems can definitely be solved in closed form via a particular bivariate confluent hypergeometric function.
Abstract: A purely analytical extension of flattened Gaussian beams [Opt. Commun.107, 335 (1994)OPCOB80030-401810.1016/0030-4018(94)90342-5] to any values of beam order is here proposed. Due to it, the paraxial propagation problem of axially symmetric, coherent flat-top beams through arbitrary ABCD optical systems can definitely be solved in closed form via a particular bivariate confluent hypergeometric function.
TL;DR: In this article , the multispectral filter design problem for spectral ranges where a viewing subspace is not defined is addressed, and the methodology of color filter design is extended to this case, which allows the optimization of custom filter transmittance that meets the physical constraints of available fabrication methods.
Abstract: This paper addresses the multispectral filter design problem for spectral ranges where a viewing subspace is not defined. The methodology of color filter design is extended to this case, which allows the optimization of custom filter transmittance that meets the physical constraints of available fabrication methods. Multispectral shortwave infrared filters are then designed for two scenarios: spectral reconstruction and false-color representation. The Monte Carlo method is used to verify the filter performance degradation due to deviations in fabrication. The results obtained indicate that the proposed method is useful for designing multispectral filters to be fabricated using generic processes without any additional constraints.
TL;DR: In this paper , a model-based approach is presented to comprehensively model nonlinear optical microscopy in scattering media, including signal generation, radiation, and far-field detection.
Abstract: The development and application of nonlinear optical (NLO) microscopy methods in biomedical research have experienced rapid growth over the past three decades. Despite the compelling power of these methods, optical scattering limits their practical use in biological tissues. This tutorial offers a model-based approach illustrating how analytical methods from classical electromagnetism can be employed to comprehensively model NLO microscopy in scattering media. In Part I, we quantitatively model focused beam propagation in non-scattering and scattering media from the lens to focal volume. In Part II, we model signal generation, radiation, and far-field detection. Moreover, we detail modeling approaches for major optical microscopy modalities including classical fluorescence, multi-photon fluorescence, second harmonic generation, and coherent anti-Stokes Raman microscopy.
TL;DR: In this paper , the authors present a feature issue to follow the conclusion of the Optica Topical Meeting on Digital Holography and 3D Imaging (DH+3D).
Abstract: This feature issue is a continuation of a tradition to follow the conclusion of the Optica Topical Meeting on Digital Holography and 3D Imaging (DH+3D). It addresses current research topics in digital holography and 3D imaging that are also in line with the topics of Applied Optics and Journal of the Optical Society of America A.
TL;DR: In this paper , a method based on a deep learning approach is proposed for direct estimation of the phase gradient without the requirement of phase unwrapping and numerical differentiation operations, which can be used for imaging different biological cells using diffraction phase microscopy setup.
Abstract: In quantitative phase microscopy, measurement of the phase gradient is an important problem for biological cell morphological studies. In this paper, we propose a method based on a deep learning approach that is capable of direct estimation of the phase gradient without the requirement of phase unwrapping and numerical differentiation operations. We show the robustness of the proposed method using numerical simulations under severe noise conditions. Further, we demonstrate the method's utility for imaging different biological cells using diffraction phase microscopy setup.
TL;DR: In this article , the authors modeled discrimination thresholds for object colors under different lighting environments and trained convolutional neural networks (CNNs) using 160,280 images labeled by either the ground-truth or human responses.
Abstract: We modeled discrimination thresholds for object colors under different lighting environments [J. Opt. Soc. Am. 35, B244 (2018)]. First, we built models based on chromatic statistics, testing 60 models in total. Second, we trained convolutional neural networks (CNNs), using 160,280 images labeled by either the ground-truth or human responses. No single chromatic statistics model was sufficient to describe human discrimination thresholds across conditions, while human-response-trained CNNs nearly perfectly predicted human thresholds. Guided by region-of-interest analysis of the network, we modified the chromatic statistics models to use only the lower regions of the objects, which substantially improved performance.
TL;DR: In this article , an optical-cryptographic system based on a new image self-disordering algorithm (ISDA) was proposed. But the system is not secure against the chosen-plaintext attack (CPA) and the known-plain text attack (KPA), since the ISDA operates the optical cipher.
Abstract: This paper demonstrates a novel optical-cryptographic system based on a new image self-disordering algorithm (ISDA). The cryptographic stage is based on an iterative procedure using an ordering sequence from the input data to produce diffusion and confusion keys. Our system uses this approach over plaintext and optical cipher from a 2f-coherent processor working with two random phase masks. Since the keys used for encryption depend on the initial input information, the system is resistant to common attacks such as the chosen-plaintext attack (CPA) and the known-plaintext attack (KPA). In addition, since the ISDA operates the optical cipher, the 2f processor linearity is destroyed, producing an enhanced ciphertext in phase and amplitude, improving optical encryption protection. This new approach offers higher security and efficiency than other reported systems. We perform security analyses and validate the feasibility of this proposal by synthesizing an experimental keystream and performing color image encryption.
TL;DR: The analytical form of the intrinsic aberration coefficients for spherical plane-symmetric optical systems expressed as a function of first-order system parameters and the paraxial chief and marginal ray angles and heights was presented in this paper .
Abstract: This paper presents the analytical form of the intrinsic aberration coefficients for spherical plane-symmetric optical systems expressed as a function of first-order system parameters and the paraxial chief and marginal ray angles and heights. The derived aberration coefficients are in the third and fourth groups with the multiplication of two or three vector products of pupil and field vectors.
TL;DR: Pancharatnam's work has been misinterpreted as referring to an evolution of states of polarization, just as Berry's work focused on a cycle of states as discussed by the authors , even though this consideration does not appear in the original work.
Abstract: While Pancharatnam discovered the geometric phase in 1956, his work was not widely recognized until its endorsement by Berry in 1987, after which it received wide appreciation. However, because Pancharatnam's paper is unusually difficult to follow, his work has often been misinterpreted as referring to an evolution of states of polarization, just as Berry's work focused on a cycle of states, even though this consideration does not appear in Pancharatnam's work. We walk the reader through Pancharatnam's original derivation and show how Pancharatnam's approach connects to recent work in geometric phase. It is our hope to make this widely cited classic paper more accessible and better understood.