Skin oxygenation level is an important indicator for the anesthesiology and psychophysiology of a wide range of skin diseases. The non-contact patient monitoring approaches rely on traditional least square method which are not accurate and can’t be deployed in clinical practices. In this paper, we exploited the power of deep learning to measure the skin oxygenation level from 16 channel spectral filter array cameras (SFA). Our architecture named SpectraNet consist of three important block i.e. a chain of Convolutional Neural Network (CNN) for feature extraction from the spectral data, an channel attention network for selecting the most informative channel selection and a bidirectional Long-Short Term Memory (LSTM) for incorporating the spatial and temporal information for estimating the final oxygenation curve from the input multi-spectral video. To show the validity of our proposed network, a clinically practiced oxygenation monitoring method (INVOS) is used as the reference. The subjective and objective evaluation shows that the techniques achieve promising results and can be deployed in the clinical practices. Moreover, due to a highly optimized nature of the proposed network, a fully trained model can be incorporated in a smartphone app for a real-time oxygenation measurement.

This paper identifies the drivers that enable spectral reproduction today and have the ability to increase its usage in the future. Different use cases of spectral reproduction in the field of colour imaging are discussed along with some of the possible workflows. Some workflows are further divided into input, spectral processing and output units as an example, such that the individual spectral processing units that can be encoded in an ICC profile can be identified. It also gives a map of how some common processing elements can be connected in order to constitute a spectral reproduction system.

A hyperspectral imaging microscope system (HIMS) was recently designed for color truth establishment of histological tissue slides used for whole slide imaging (WSI) systems color performances assessment. Here, we present the estimation procedure of the colorimetrical performance of the HIMS by measuring the transmittance spectra of spatially uniform neutral density and color filters and deriving the color coordinates in the CIELAB color space. The transmittance and CIELAB results are compared to reference transmittance spectra and subsequent CIELAB coordinates provided by measurement of the same region of interest with a spectroradiometer. To measure the same region of interest, the spectroradiometer is equipped with a fiber probe whose tip is set in one of the eyepiece tubes of the microscope. The CIE 1976 color difference, ΔE^*_ab, is the metric used for goodness estimation.

Content created in High Dynamic Range (HDR) and Wide Color Gamut (WCG) is becoming more ubiquitous, driving the need for reliable tools for evaluating the quality across the imaging ecosystem. One of the simplest techniques to measure the quality of any video system is to measure the color errors. The traditional color difference metrics such as ΔE₀₀ and the newer HDR specific metrics such as ΔE_Z and ΔE_ITP compute color difference on a pixel-by-pixel basis which do not account for the spatial effects (optical) and active processing (neural) done by the human visual system. In this work, we improve upon the per-pixel ΔE_ITP color difference metric by performing a spatial extension similar to what was done during the design of S-CIELAB. We quantified the performance using four standard evaluation procedures on four publicly available HDR and WCG image databases and found that the proposed metric results in a marked improvement with subjective scores over existing per-pixel color difference metrics.

Recently, an iterative optimization method was proposed that determines the spectral transmittance of a color filter which, when placed in front of a camera, makes the camera more colorimetric [1]. However, the performance of this method depends strongly on the filter (guess) that initializes the optimization. In this paper, we develop a simple extension to the optimization where we systematically sample the set of possible initial filters and for each initialization solve for the best refinement. Experiments demonstrate that improving the initialization step can result in the effective ‘camera+filter’ imaging system being much more colorimetric. Moreover, the filters we design are smoother than previously reported (which makes them easier to manufacture).

There are not many international courses that teach color science applied to non-technical fields. Here, we want to present the experience from a master course organized by Gruppo del Colore – Associazione Italiana Colore and Politecnico of Milano: the Master in Color Design & Technology. It has the aim of training students in the use of color mainly for design purposes, and color science and colorimetry have a big role in the program. The Master is organized in three main phases: Fundamentals, Project Works and Internship. The first part is a series of lectures and frontal lessons that gives to the students the theorical and technical bases to be used in project works practical applications of and internship. In fact, in the second and third parts students are asked to design and develop different applicative design projects. After the first part of Fundamentals training, students will be able to manage disciplines such as colorimetry, visual perception, physics, chemistry, optics and psychology, to build up their future professional career in different fields.

FM (Frequency modulation) halftoning (aperiodic and dispersed-dots) is increasingly popular with traditional analog offset lithographic printing. There is a desire from customers in the commercial market to use this capability with high-end digital presses based on electrophotographic printing (EP) technologies. However, the inherent instability of the EP process challenges the achievement of satisfactory print quality with dispersed-dot, aperiodic halftoning. The direct binary search (DBS) algorithm is widely considered to represent the gold standard of dispersed-dot, aperiodic halftone image quality. In this paper, we continue our previous efforts to adapt DBS from dispersed-dots to clustered-dots to use with the Indigo liquid EP printing technology; we present a new screen design algorithm for aperiodic, clustered-dot halftoning based on Direct Bineary Search. Our screen design has a very good detail rendering capability and very stable halftone frequency overall. The halftone texture after applying screen is even better than directly using our previous work, clustered-dot halftoning.

An alignment approach for data-bearing halftone images, which are a visually pleasant alternative to barcodes, is proposed in this paper. In this paper, we address the alignment problem of data-bearing halftone images on a 3D surface. Different types of surfaces have been tested , using our proposed approach, and high accuracy results have been achieved. Additionally, we also develop a data retrieval tool from an aligned image, in order to decode the data embedded in the original image. A system to assess the accuracy of alignment is introduced to quantify the effectiveness of the proposed alignment approach.

Spot colors are widely used in the food packaging industry. We wish to add a watermark signal within a spot color that is readable by a Point Of Sale (POS) barcode scanner which typically has red illumination. Some spot colors such as blue, black and green reflect very little red light and are difficult to modulate with a watermark at low visibility to a human observer. The visibility measurements that have been made with the Digimarc watermark enables the selection of a complementary color to the base color which can be detected by a POS barcode scanner but is imperceptible at normal viewing distance.