Characterization method for a multispectral high-dynamic-range imaging system

Most recent bidirectional reflectance distribution function (BRDF) measurement systems are the image-based that consist of a light source, a detector, and curved samples. They are useful for measuring the reflectance properties of a material but they have two major drawbacks. They suffer from high cost of BRDF acquisition and also give inaccurate results due to the limited use of spectral bands. In this paper, we propose a novel multispectral HDR imaging system and its efficient characterization method. It combines two promising technologies: high dynamic range (HDR) imaging and multispectral imaging to measure BRDF. We perform a full spectral recovery using camera response curves for each wavelength band and its analysis. For this, we use an HDR camera to capture HDR images and a liquid crystal tunable filter (LCTF) to generate multi-spectral images. Our method can provide an accurate color reproduction of metameric objects as well as a saturated image. Our multi-spectral HDR imaging system provides a very fast data acquisition time and also gives a low system setup cost compared to previous multi-spectral imaging systems and point-based commercial spectroradiometers. We verify the color accuracy of our multi-spectral HDR imaging system in terms of human vision and metamerism using colorimetric and spectral metric.

in vivo multispectral imaging (MSI) increases the sensitivity and usefulness of small animal models of development and disease, including the most popular and promising experimental systems. In mice, MSI can essentially eliminate autofluorescence that otherwise limits sensitivity, reducing detection limits by as much as 100-fold. Fluorescence imaging is a key technology for determining the where, the when and the how much of gene expression. However, the ability to image and quantitate fluorescently labeled markers in vivo has typically been limited by the bright autofluorescence of animal tissues. Small-animal imaging, which often means the imaging of mouse models, encounters autofluorescence primarily from components in skin (collagen, which fluoresces green) and food (chlorophyll, which fluoresces red). However, other small animal model systems, such as nematodes (C. elegans), zebrafish (D. rerio) embryos or adult fish, and fruit flies (D. melanogaster) pose similar problems due to the presence of autofluorescent structures that may render common labeling strategies, including the use of green fluorescent protein (GFP) labels, problematic. Various solutions have been proposed for the reduction or elimination of autofluorescence. The most prevalent is simply to use narrow bandpass emission filters in an effort to isolate the desired fluorescence signal [1]. More recently, there has been a move to use infrared-emitting labels that are excited at wavelengths that are much less likely to induce autofluorescence signals. However, autofluorescence still limits sensitivity. Fortunately, the low signal-to-background contrast problem created by autofluorescence can be substantially eliminated using MSI techniques. Moreover, MSI permits the simultaneous use of multiple labels, such as GFP and RFP, even when they spectrally overlap with themselves or autofluorescence [2]. Presented here are the results of applying an MSI strategy to the whole-animal in vivo imaging of mice, C. elegans, D. rerio and D. melanogaster at a variety of magnifications, ranging from the imaging of three whole mice simultaneously down to microscopic images of whole animals and embryos. This is accomplished using a liquid crystal tunable filter (LCTF)-based imaging system that has been adapted to either a C-mount on a fluorescence microscope or macroscope, or incorporated into a whole-animal imaging system. In each case, the sensitivity of the fluorescence measurement was greatly improved by using a MSI approach. Rapid, quantitative, imaging of GFP signals of up to a few hundred flies simultaneously in a few seconds can be easily achieved, as can high-sensitivity microscopic imaging of GFP in nematode worms. These types of imaging experiments are of value to anyone with whole-animal fluorescence-based models. [1] Niswender KD et al, J Microsc 180, 109-116 (1995) [2] Levenson, et al, Cytometry A. 2006 Aug; 69(8):748-58 Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3236.

Spectral imaging including machine vision and multispectral imaging can provide a rapid, nondestructive means to assess agricultural commodities for their quality and safety for human consumption. These nondestructive techniques generally rely on reflectance measurements; the most commonly used spectral regions range through the visible (Vis) to the near infrared (NIR). Another optical sensing technique is based on fluorescence that is generally regarded as more sensitive optical sensing tools compared to reflectance techniques. Recently, we developed two imaging systems for food safety research; a laboratory-based hyperspectral imaging system capable of both reflectance and fluorescence measurements and a multispectral laser induced fluorescence imaging system. Because many contiguous spectral bands are acquired with each hyperspectral image pixel, the resulting data quantity makes uses of hyperspectral imaging spectrometer for on-line food safety inspection impractical. Instead, the spectral and spatial information is used to determine several optimal wavebands that can be implemented to a multispectral imaging system. We present a systematic method for using hyperspectral image data to identify few wavebands to be used in multispectral detection systems. Also presented is a two-band ratio as a multispectral fusion method along with automated detection for animal feces contamination on apples. The fluorescence imaging techniques demonstrated that even minute animal feces, not clearly visible to human eye, could be detected. Practical considerations for development of multispectral fluorescence imaging systems for on-line uses are also discussed.

We report a spectrally and temporally programmable light engine based on a spatial light modulator that can dynamically create any narrow or broadband spectral profile for hyperspectral, fluorescence, or principal component imaging. Most hyperspectral or multispectral imaging systems use wavelength selection devices such as acousto-optic tunable filters (AOTFs), tunable grating or prism-based monochromators, or filter wheels. While these devices can select wavelengths they cannot create arbitrary spectral profiles. This simple and economical system can be controlled at high speed (up to 5000 illumination profiles per second). Digitally controlled illumination is bit additive with image data providing high dynamic range imaging with monochrome or color imaging devices. This is especially advantageous for endoscopes employing small well CCD or CMOS sensors since the dynamic range now can extend beyond the limits of the sensor itself. In this report we show multispectral images of in vivo tissue and in vitro tissue samples using endoscopes, surgical microscopes and conventional microscopes.

In recent years, endoscopic imaging has become the major diagnostic approach for early cancer. It is difficult to accurately obtain the information of lesions and components content by using conventional white light imaging (C-WLI). Multispectral imaging techniques such as narrowband imaging are widely used in endoscopic clinical because of their specificity on the surface structure of digestive tract mucosa. However, there is still a lack of multispectral techniques for tissue components specificity. Tissue components such as lipid, hemoglobin are closely related to the generation and development of tumors, but it is difficult to observe the characteristics of lipid and hemoglobin by conventional white light imaging. Therefore, we studied the multispectral endoscopic imaging technique for the analysis of digestive tract mucosal components. Based on the reflectance spectrum characteristics of these tissue components, we determined their specific wavelength, and comprehensively considered the absorption, scattering, oxygenation and others in order to determine the most appropriate optical band in the wavelength range of 365-660nm. Through experimental verification, we choose different narrow-band wavelength combinations for lipids and hemoglobin oxygen saturation respectively to achieve multispectral imaging. In order to simulate the optical properties of digestive tract surface, we made tissue optical phantom. At the same time, we tested and optimized the imaging system and algorithm by the experiments in vitro, and obtained the optimal multispectral image of tissue components, then realize the quantitative detection combined with the content analysis algorithm. Our pilots show that the multispectral imaging system can improve the contrast of endoscopy image, enhance the detail information, achieve high precision detection of tissue components content, and control the error within 10%.

A five-band multispectral(MIS)imaging system has been constructed and tested by the Hughes Research Laboratories. It has five boresighted sensors mounted on a scanning pedestal in a completely mobile and self-contained instrumentation trailer. The systems are .8μ passive, 1.06μ active/ranging, 10.6μ active, 8-12μ passive and 95 GHz (3.2 mm) active/ranging. The MIS operates in all weather conditions and produces registered, calibrated and digitized 12-bit raster scanned imagery. Designed as a sensor test bed for DARPA, the MIS is a versatile and adaptable system, which has potential use for a wide range of imaging and non-imaging applications. Field tests conducted in Culver City, California and Climax, Colorado will be discussed and the applicability of the MIS to the acquisition and analysis of more diverse scenes will be discussed.

Focus on lasers and imaging

Ghost detection and removal for high dynamic range images: Recent advances

Multispectral imaging technique has been used for skin analysis, especially for in-vivo non contact mapping of skin's chromophores. It is implemented by analyzing spectral cube data, i.e. a spatial image data that are taken at different wavelength. The acquired cube data is then used to construct 2-D maps of the distributed concentrations of chromophores, i.e. oxy-/deoxy-haemoglobin and melanin. The developmental goal of measurement device is to help dermatologist with an accurate tool for perform analysis on patient's skin condition. In this paper efforts to develope and characterize a new multispectral imaging (MSI) system for dermatology application will be described. The system developed system is operated using 12 wavelengths between 350 and 970 nm, at an equally wavelength intervals. The system composed of two parts: i.e. a) the light source, constructed using LEDs with 12 different wavelenghts in an dome-shaped compartment, and b) a monochromatic 8-Bit CCD camera, equipped with C-Mount objective lens, for capturing skin images under different illuminating wavelengths. A dedicated software to control the system, i.e. for acquired and processing multispectral images, were developed based on GUI MATLAB. Characterization were done to examined the inherent properties of the developed multispectral system, both for the light source (spectral bands of the LEDs used) and for the camera (spatial uniformity, linearity, and resolution). The multispectral imaging system is capable to construct 2-D map of distributed concentrations of chromophores from a skin surface in less than 6 seconds, which is regarded as suitable for daily clinical practice.

Study on the detection of three-dimensional soot temperature and volume fraction fields of a laminar flame by multispectral imaging system

A simultaneous multispectral fluorescence imaging system incorporating multiplexed volume holographic grating (VHG) is developed to acquire multispectral images of an object in one shot. With the multiplexed VHG, the imaging system can provide the distribution and spectral characteristics of multiple fluorophores in the scene. The implementation and performance of the simultaneous multispectral imaging system are presented. Further, the system’s capability in simultaneously obtaining multispectral fluorescence measurements is demonstrated with in vivo experiments on a mouse. The demonstrated imaging system has the potential to obtain multispectral images fluorescence simultaneously.

Multispectral imaging, which extends the number of imaging channels beyond the conventional three, has demonstrated to be beneficial for a wide range of applications. Its ability of acquiring images beyond the visible range and applicability in many different application domains lead to the design and the development of a number of multispectral imaging technologies and systems. Given different systems to choose from, it is important to be able to compare them in a general and in many situations specific to a certain application of interest. In this paper, we evaluate several conventional and recently proposed multispectral imaging systems, both qualitatively and quantitatively. Both spectral and colorimetric accuracies are used as the criteria in the quantitative evaluation. The systems are evaluated and compared for two specific applications: imaging of natural scenes and paintings (cultural heritage), as well as for a general spectral imaging solution. This work provides a framework for the evaluation and comparison of different multispectral imaging systems, which we believe, would be very helpful in identifying the most appropriate technique or system for a given application.

Whilst radiotherapy (RT) is widely used for cancer treatment, radiodermatitis caused by RT is one most common severe side effect affecting 95% cancer patients. Accurate radiodermatitis assessment and classification is essential to adopt timely treatment, management and monitoring, which all depend on reliable and objective tools for radiodermatitis grading. We therefore, in this work, reported the development and grading performance validation of a low-cost (∼2318.2 CNY) algorithms-based hyperspectral imaging (aHSI) system for radiodermatitis assessment. The low-cost aHSI system was enabled through Monte Carlo (MC) simulations conducted on multi-spectra acquired from a custom built low-cost multispectral imaging (MSI) system, deriving algorithms-based hyper-spectra with spectral resolution of 1 nm. The MSI system was based on sequentially illuminated narrow-band light-emitting diodes (LEDs) and a CMOS camera. Erythema induced artificially on healthy volunteers was measured by the aHSI system developed, with algorithms-based hyper-spectra and skin layer resolved physiological parameters (i.e., the blood volume fraction (BVF) and the oxygen saturation of hemoglobin in blood, et. al.) derivation using MC simulations. The MC simulations derived BVF and the oxygen saturation of hemoglobin in blood showed significant (P < 0.001, analysis of variance: ANOVA) increase with erythema. Further 1D-convolution neural network (CNN) implemented on the algorithms-based hyper-spectra leads to an overall classification accuracy of 93.1%, suggesting the great potential of low-cost aHSI system developed for radiodermatitis assessment.

Using conventional camera to capture natural scenes with high dynamic range generally results in saturation as well as underexposure, because of their limited dynamic range. And moreover, the image of conventional RGB camera with RGB color filter lacks color accuracy. We present a promising solution - a high dynamic range multispectral camera placing a Liquid Crystal Tunable Filter (LCTF) between lens and gray level imaging sensor. For each bands, gray level images with different exposures are acquired separately and are combined into a multispectral high dynamic range image afterwards. The high dynamic range multispectral image has higher color accuracy and greater dynamic range than the images of the traditional RGB camera.

Multispectral single shot imaging systems can benefit computer vision applications in needs of a compact and affordable imaging system. Spectral filter arrays technology meets the requirement, but can lead to artifacts due to inhomogeneous intensity levels between spectral channels due to filter manufacturing constraints, illumination and object properties. One solution to solve this problem is to use high dynamic range imaging techniques on these sensors. We define a spectral imaging pipeline that incorporates high dynamic range, demosaicing and color image visualization. Qualitative evaluation is based on real images captured with a prototype of spectral filter array sensor in the visible and near infrared.