Spectrally stable ink variability in a multi-primary printer

It was shown previously that a multi-ink printer can reproduce spectral reflectances within a specified tolerance range using many distinct ink combinations. An algorithm was developed to systematically analyze a printer to determine the amount of multi-ink variability throughout its spectral gamut. The advantage of this algorithm is that any spectral difference metric can be used as the objective function. Based on the results of the analysis for one spectral difference metric, six-dimensional density map displays were constructed to illustrate the amount of spectral redundancy throughout the ink space. One CMYKGO ink-jet printer was analyzed using spectral reflectance factor RMS as the spectral difference metric and selecting 0.02 RMS as the tolerance limit. For these parameters, the degree of spectral matching freedom for the printer reduced to five inks because the chromatic inks were able to reproduce spectra within the 0.02 tolerance limit throughout the printer\u27s gamut. Experiments were designed to exploit spectrally stable multi-ink variability within the analyzed printer. The first experiment used spectral redundancy to visually evaluate spectral difference metrics. Using the developed database of spectrally similar samples allows any spectral difference metric to be compared to a visual response. The second experiment demonstrated the impact of spectral redundancy on spectral color management. Typical color image processing techniques use profiles consisting of sparse multi-dimensional lookup tables that interpolate between adjacent nodes to prepare an image for rendering. It was shown that colorimetric error resulted when interpolating between lookup table nodes that were inconsistent in digital count space although spectrally similar. Finally, the analysis was used to enable spectral watermarking of images. To illustrate the significance of this watermarking technique, information was embedded into three images with varying levels of complexity. Prints were made verifying that information could be hidden while preserving the visual and spectral integrity of the original image

Navigating the roadblocks to spectral color reproduction: data-efficient multi-channel imaging and spectral color management

Commercialization of spectral imaging for color reproduction will require the identification and traversal of roadblocks to its success. Among the drawbacks associated with spectral reproduction is a tremendous increase in data capture bandwidth and processing throughput. Methods are proposed for attenuating these increases with data-efficient methods based on adaptive multi-channel visible-spectrum capture and with low-dimensional approaches to spectral color management. First, concepts of adaptive spectral capture are explored. Current spectral imaging approaches require tens of camera channels although previous research has shown that five to nine channels can be sufficient for scenes limited to pre-characterized spectra. New camera systems are proposed and evaluated that incorporate adaptive features reducing capture demands to a similar few channels with the advantage that a priori information about expected scenes is not needed at the time of system design. Second, proposals are made to address problems arising from the significant increase in dimensionality within the image processing stage of a spectral image workflow. An Interim Connection Space (ICS) is proposed as a reduced dimensionality bottleneck in the processing workflow allowing support of spectral color management. In combination these investigations into data-efficient approaches improve two critical points in the spectral reproduction workflow: capture and processing. The progress reported here should help the color reproduction community appreciate that the route to data-efficient multi-channel visible spectrum imaging is passable and can be considered for many imaging modalities

Expanding Dimensionality in Cinema Color: Impacting Observer Metamerism through Multiprimary Display

Television and cinema display are both trending towards greater ranges and saturation of reproduced colors made possible by near-monochromatic RGB illumination technologies. Through current broadcast and digital cinema standards work, system designs employing laser light sources, narrow-band LED, quantum dots and others are being actively endorsed in promotion of Wide Color Gamut (WCG). Despite artistic benefits brought to creative content producers, spectrally selective excitations of naturally different human color response functions exacerbate variability of observer experience. An exaggerated variation in color-sensing is explicitly counter to the exhaustive controls and calibrations employed in modern motion picture pipelines. Further, singular standard observer summaries of human color vision such as found in the CIE’s 1931 and 1964 color matching functions and used extensively in motion picture color management are deficient in recognizing expected human vision variability. Many researchers have confirmed the magnitude of observer metamerism in color matching in both uniform colors and imagery but few have shown explicit color management with an aim of minimized difference in observer perception variability. This research shows that not only can observer metamerism influences be quantitatively predicted and confirmed psychophysically but that intentionally engineered multiprimary displays employing more than three primaries can offer increased color gamut with drastically improved consistency of experience. To this end, a seven-channel prototype display has been constructed based on observer metamerism models and color difference indices derived from the latest color vision demographic research. This display has been further proven in forced-choice paired comparison tests to deliver superior color matching to reference stimuli versus both contemporary standard RGB cinema projection and recently ratified standard laser projection across a large population of color-normal observers

Neural Networks for Hyperspectral Imaging of Historical Paintings: A Practical Review

Hyperspectral imaging (HSI) has become widely used in cultural heritage (CH). This very efficient method for artwork analysis is connected with the generation of large amounts of spectral data. The effective processing of such heavy spectral datasets remains an active research area. Along with the firmly established statistical and multivariate analysis methods, neural networks (NNs) represent a promising alternative in the field of CH. Over the last five years, the application of NNs for pigment identification and classification based on HSI datasets has drastically expanded due to the flexibility of the types of data they can process, and their superior ability to extract structures contained in the raw spectral data. This review provides an exhaustive analysis of the literature related to NNs applied for HSI data in the CH field. We outline the existing data processing workflows and propose a comprehensive comparison of the applications and limitations of the various input dataset preparation methods and NN architectures. By leveraging NN strategies in CH, the paper contributes to a wider and more systematic application of this novel data analysis method

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Advancing fluorescent contrast agent recovery methods for surgical guidance applications

Fluorescence-guided surgery (FGS) utilizes fluorescent contrast agents and specialized optical instruments to assist surgeons in intraoperatively identifying tissue-specific characteristics, such as perfusion, malignancy, and molecular function. In doing so, FGS represents a powerful surgical navigation tool for solving clinical challenges not easily addressed by other conventional imaging methods. With growing translational efforts, major hurdles within the FGS field include: insufficient tools for understanding contrast agent uptake behaviors, the inability to image tissue beyond a couple millimeters, and lastly, performance limitations of currently-approved contrast agents in accurately and rapidly labeling disease. The developments presented within this thesis aim to address such shortcomings. Current preclinical fluorescence imaging tools often sacrifice either 3D scale or spatial resolution. To address this gap in high-resolution, whole-body preclinical imaging tools available, the crux of this work lays on the development of a hyperspectral cryo-imaging system and image-processing techniques to accurately recapitulate high-resolution, 3D biodistributions in whole-animal experiments. Specifically, the goal is to correct each cryo-imaging dataset such that it becomes a useful reporter for whole-body biodistributions in relevant disease models. To investigate potential benefits of seeing deeper during FGS, we investigated short-wave infrared imaging (SWIR) for recovering fluorescence beyond the conventional top few millimeters. Through phantom, preclinical, and clinical SWIR imaging, we were able to 1) validate the capability of SWIR imaging with conventional NIR-I fluorophores, 2) demonstrate the translational benefits of SWIR-ICG angiography in a large animal model, and 3) detect micro-dose levels of an EGFR-targeted NIR-I probe during a Phase 0 clinical trial. Lastly, we evaluated contrast agent performances for FGS glioma resection and breast cancer margin assessment. To evaluate glioma-labeling performance of untargeted contrast agents, 3D agent biodistributions were compared voxel-by-voxel to gold-standard Gd-MRI and pathology slides. Finally, building on expertise in dual-probe ratiometric imaging at Dartmouth, a 10-pt clinical pilot study was carried out to assess the technique’s efficacy for rapid margin assessment. In summary, this thesis serves to advance FGS by introducing novel fluorescence imaging devices, techniques, and agents which overcome challenges in understanding whole-body agent biodistributions, recovering agent distributions at greater depths, and verifying agents’ performance for specific FGS applications

Advances in Hyperspectral and Multispectral Optical Spectroscopy and Imaging of Tissue

The purpose of this SI is to provide an overview of recent advances made in the methods used for tissue imaging and characterization, which benefit from using a large range of optical wavelengths. Guerouah et al. has contributed a profound study of the responses of the adult human brain to breath-holding challenges based on hyperspectral near-infrared spectroscopy (hNIRS). Lange et al. contributed a timely and comprehensive review of the features and biomedical and clinical applications of supercontinuum laser sources. Blaney et al. reported the development of a calibration-free hNIRS system that can measure the absolute and broadband absorption and scattering spectra of turbid media. Slooter et al. studied the utility of measuring multiple tissue parameters simultaneously using four optical techniques operating at different wavelengths of light—optical coherence tomography (1300 nm), sidestream darkfield microscopy (530 nm), laser speckle contrast imaging (785 nm), and fluorescence angiography (~800 nm)—in the gastric conduit during esophagectomy. Caredda et al. showed the feasibility of accurately quantifying the oxy- and deoxy-hemoglobin and cytochrome-c-oxidase responses to neuronal activation and obtaining spatial maps of these responses using a setup consisting of a white light source and a hyperspectral or standard RGB camera. It is interest for the developers and potential users of clinical brain and tissue optical monitors, and for researchers studying brain physiology and functional brain activity

Planetary Biology and Microbial Ecology: Molecular Ecology and the Global Nitrogen cycle

This report summarizes the results of the Planetary Biology and Molecular Ecology's summer 1991 program, which was held at the Marine Biological Laboratory in Woods Hole, Massachusetts. The purpose of the interdisciplinary PBME program is to integrate, via lectures and laboratory work, the contributions of university and NASA scientists and student interns. The goals of the 1991 program were to examine several aspects of the biogeochemistry of the nitrogen cycle and to teach the application of modern methods of molecular genetics to field studies of organisms. Descriptions of the laboratory projects and protocols and abstracts and references of the lectures are presented

Flexible and Robust Calibration of the Yule-Nielsen Model for CMYK Prints

Spectral reflection prediction models, although effective, are impractical for certain industrial applications such as self-calibrating devices and online monitoring because of the requirements imposed by their calibration. The idea emerged to make the calibration more flexible. Instead of requiring specific color-constant calibration patches, the calibration would rely on the information contained in regular prints, e.g. on information found in printed color images. Using the CMYK Ink Spreading enhanced Yule-Nielsen modified Spectral Neugebauer model (IS-YNSN), the objective of this dissertation is to recover the Neugebauer primaries and ink spreading curves from image tiles extracted from printed color images. The IS-YNSN is first reviewed in the context of CMYK prints. Two sources of ambiguity are identified and removed, yielding a more robust model better suited for a flexible calibration. We then propose a gradient-descent method to acquire the ink spreading curves from image tiles by relying on constraints based on a metric evaluating the relevance of each ink spreading curve to the set of image calibration tiles. We optimize the algorithm which automatically selects the image tiles to be extracted and show that 5 to 10 well-chosen image tiles are sufficient to accurately acquire all the ink spreading curves. The flexible calibration is then extended to recover the Neugebauer primaries from printed color images. Again, a simple gradient-descent algorithm is not sufficient. Thanks to a set of constraints based on Principal Component Analysis (PCA) and the relationships between composed Neugebauer primaries and the ink transmittances, good approximations of the Neugebauer primaries are achieved. These approximations are then optimized, yielding an accurately calibrated IS-YNSN model comparable to one obtained by classical calibrations. A detailed analysis of these calibrations shows that 25 well-chosen CMYK image calibration tiles are sufficient to accurately recover both the Neugebauer primaries and the ink spreading curves