Application of PQS for image quality analysis in visible spectral imaging

An image quality investigation in visible spectral imaging was performed. Spectral images were simulated using different number of imaging channels, wavelength steps, and noise levels based on practical spectral imaging systems. A mean opinion score (MOS) was determined from a subjective visual assessment scale experiment for image quality of spectral images rendered to a three-channel display. A set of partial image distortion measures, including color difference for color images, were defined based on classified and quantified actual distortions produced by spectral imaging systems. Principal components analysis was then carried out to quantify the correlation between distortion factors. Finally, a multiple regression analysis (MRA) was carried out between the principal component vectors and the measured MOS values to determine the picture quality scale (PQS). The obtained quality metric, PQS, had high correlation with the subjective measure, MOS. The importance of contribution of the distortion factors in the image quality metric was also evaluated

One-shot ultraspectral imaging with reconfigurable metasurfaces

One-shot spectral imaging that can obtain spectral information from thousands of different points in space at one time has always been difficult to achieve. Its realization makes it possible to get spatial real-time dynamic spectral information, which is extremely important for both fundamental scientific research and various practical applications. In this study, a one-shot ultraspectral imaging device fitting thousands of micro-spectrometers (6336 pixels) on a chip no larger than 0.5 cm$^2$, is proposed and demonstrated. Exotic light modulation is achieved by using a unique reconfigurable metasurface supercell with 158400 metasurface units, which enables 6336 micro-spectrometers with dynamic image-adaptive performances to simultaneously guarantee the density of spectral pixels and the quality of spectral reconstruction. Additionally, by constructing a new algorithm based on compressive sensing, the snapshot device can reconstruct ultraspectral imaging information ($\Delta\lambda$/$\lambda$~0.001) covering a broad (300-nm-wide) visible spectrum with an ultra-high center-wavelength accuracy of 0.04-nm standard deviation and spectral resolution of 0.8 nm. This scheme of reconfigurable metasurfaces makes the device can be directly extended to almost any commercial camera with different spectral bands to seamlessly switch the information between image and spectral image, and will open up a new space for the application of spectral analysis combining with image recognition and intellisense

Utility Analysis for Optimizing Compact Adaptive Spectral Imaging Systems for Subpixel Target Detection Applications

Since the development of spectral imaging systems where we transitioned from panchromatic, single band images to multiple bands, we have pursued a way to evaluate the quality of spectral images. As spectral imaging capabilities improved and the bands collected wavelengths outside of the visible spectrum they could be used to gain information about the earth such as material identification that would have been a challenge with panchromatic images. We now have imaging systems capable of collecting images with hundreds of contiguous bands across the reflective portion of the electromagnetic spectrum that allows us to extract information at subpixel levels. Prediction and assessment methods for panchromatic image quality, while well-established are continuing to be improved. For spectral images however, methods for analyzing quality and what this entails have yet to form a solid framework. In this research, we built on previous work to develop a process to optimize the design of spectral imaging systems. We used methods for predicting quality of spectral images and extended the existing framework for analyzing efficacy of miniature systems. We comprehensively analyzed utility of spectral images and efficacy of compact systems for a set of application scenarios designed to test the relationships of system parameters, figures of merit, and mission requirements in the trade space for spectral images collected by a compact imaging system from design to operation. We focused on subpixel target detection to analyze spectral image quality of compact spaceborne systems with adaptive band selection capabilities. In order to adequately account for the operational aspect of exploiting adaptive band collection capabilities, we developed a method for band selection. Dimension reduction is a step often employed in processing spectral images, not only to improve computation time but to avoid errors associated with high dimensionality. An adaptive system with a tunable filter can select which bands to collect for each target so the dimension reduction happens at the collection stage instead of the processing stage. We developed the band selection method to optimize detection probability using only the target reflectance signature. This method was conceived to be simple enough to be calculated by a small on-board CPU, to be able to drive collection decisions, and reduce data processing requirements. We predicted the utility of the selected bands using this method, then validated the results using real images, and cross-validated them using simulated image associated with perfect truth data. In this way, we simultaneously validated the band selection method we developed and the combined use of the simulation and prediction tools used as part of the analytic process to optimize system design. We selected a small set of mission scenarios and demonstrated the use of this process to provide example recommendations for efficacy and utility based on the mission. The key parameters we analyzed to drive the design recommendations were target abundance, noise, number of bands, and scene complexity. We found critical points in the system design trade space, and coupled with operational requirements, formed a set of mission feasibility and system design recommendations. The selected scenarios demonstrated the relationship between the imaging system design and operational requirements based on the mission. We found key points in the spectral imaging trade space that indicated relationships within the spectral image utility trade space that can be used to further solidify the frameworks for compact spectral imaging systems

Design and Construction of a Multispectral Camera for Spectral and Colorimetric Reproduction

Multi-spectral imaging and spectral reflectance reconstruction can be used in cultural-heritage institutes to digitalize their collections for documentation purposes. It can be used to simulate artwork under any lighting condition, and to analyze colorants that were used. The basic idea of a multi-spectral imaging system is to sub-sample spectral reflectance factor, producing results similar to a spectrophotometer. The sampled data are used to reconstruct reflectance for the visible spectrum. In this thesis, a wide band multispectral camera was designed and constructed to achieve high spectral and color accuracy as well as high image quality. Noise propagation theory was introduced and tested. A seven channel band- pass filter set was modeled using Gaussian functions and optimized to yield high spectral and colorimetric reproduction accuracy as well as low colori- metric noise. Single and sandwich filters were selected from o!-the-shelf absorption filters using the Gaussian bandpass filter model. Experiments were conducted to test the spectral, color and noise performance of the novel sandwich filters and compared with interference filters. The novel sandwich fil- ters led to increased colorimetric accuracy along with a reduction colorimetric noise. This imaging system will be used as part of a recommended workflow for museum archiving, and will be an important addition to the spectral imaging capabilities at MCSL

On the use of a liquid lens for improving iris images quality in a hyperspectral system

In this paper, we describe how using a liquid lens can improve the quality of iris images acquired by a hyperspectral system. This improvement in the image quality is especially noticeable for systems that scan the iris over a wide range of wavelengths, e.g. visible and near-infrared spectrum. We have tested this approach on the previously developed system able to acquire iris images in the spectral range 480 - 900 nm. The key novelty presented in this paper is represented by the possibility of adaptively adjusting the focus of the imaging system, allowing for chromatic aberration compensation and ensuring a constant image sharpness among all wavelengths. A fast-tunable liquid lens has been placed in front of the chromatically corrected camera objective to adaptively change the overall focus of the imaging system. The findings imply that the device can rapidly perform hyperspectral measurements of the iris over a broad wavelength range ensuring optimal focus for all images

High-Performance Thin-Film Garnet Materials for Magneto-Optic and Nanophotonic Applications

Since the 1960\u27s, Magneto-optic (MO) garnet materials have been studied extensively. These materials can possess world-record MO performance characteristics in terms of Faraday rotation and optical quality. Among the rear-earth-doped garnets, the Bi-substituted iron garnet is the best candidate for use as a functional material in different integrated-optics, imaging/image processing applications and also in forward-looking applications e.g. the design of metamaterials with non-reciprocal properties. We have established a set of technologies for fabricating ferrimagnetic garnet films of type (BiDy)3(FeGa)5O12 and also garnet-oxide nanocomposite (BiDy)3(FeGa)5O12 : Bi2O3 layers possessing record-high MO quality across the visible spectral range using RF-magnetron sputtering and oven annealing. Our MO garnet films possess excellent optical and magnetic properties, which make them very attractive and promising for a large range of optoelectronic, photonics-related and MO imaging applications

A new multi-spectral imaging system for examining paintings

A new multispectral system developed at the National Gallery is presented. The system is capable of measuring the spectral reflectance per pixel of a painting. These spectra are found to be almost as accurate as those recorded with a spectrophotometer; there is no need for any spectral reconstruction apart from a simple cubic interpolation between measured points. The procedure for recording spectra is described and the accuracy of the system is quantified. An example is presented of the use of the system to scan a painting of St. Mary Magdalene by Crivelli. The multispectral data are used in an attempt to identify some of the pigments found in the painting by comparison with a library of spectra obtained from reference pigments using the same system. In addition, it is shown that the multispectral data can be used to render a color image of the original under a chosen illuminant and that interband comparison can help to elucidate features of the painting, such as retouchings and underdrawing, that are not visible in trichromatic images

Advances in multispectral and hyperspectral imaging for archaeology and art conservation

Multispectral imaging has been applied to the field of art conservation and art history since the early 1990s. It is attractive as a noninvasive imaging technique because it is fast and hence capable of imaging large areas of an object giving both spatial and spectral information. This paper gives an overview of the different instrumental designs, image processing techniques and various applications of multispectral and hyperspectral imaging to art conservation, art history and archaeology. Recent advances in the development of remote and versatile multispectral and hyperspectral imaging as well as techniques in pigment identification will be presented. Future prospects including combination of spectral imaging with other noninvasive imaging and analytical techniques will be discussed