Spectral Reconstruction from RGB Imagery: A Potential Option for Infinite Spectral Data?

Spectral imaging has revolutionisedvarious fields by capturing detailed spatial and spectral information. However, its high cost and complexity limit the acquisition of a large amount of data to generalise processes and methods, thus limiting widespread adoption. To overcome this issue, a body of the literature investigates how to reconstruct spectral information from RGB images, with recent methods reaching a fairly low error of reconstruction, as demonstrated in the recent literature.

Raw Spectral Filter Array Imaging for Scene Recognition.

Scene recognition is the task of identifying the environment shown in an image. Spectral filter array cameras allow for fast capture of multispectral images. Scene recognition in multispectral images is usually performed after demosaicing the raw image.

Optical and Electromechanical Design and Implementation of an Advanced Multispectral Device to Capture Material Appearance.

The application of materials with changing visual properties with lighting and observation directions has found broad utility across diverse industries, from architecture and fashion to automotive and film production. The expanding array of applications and appearance reproduction requirements emphasizes the critical role of material appearance measurement and surface characterization. Such measurements offer twofold benefits in soft proofing and product quality control, reducing errors and material waste while providing objective quality assessment.

Improving RGB illuminant estimation exploiting spectral average radiance.

We introduce a method that enhances RGB color constancy accuracy by combining neural network and -means clustering techniques. Our approach stands out from previous works because we combine multispectral and color information together to estimate illuminants. Furthermore, we investigate the combination of the illuminant estimation in the RGB color and in the spectral domains, as a strategy to provide a refined estimation in the RGB color domain.

Additivity Constrained Linearisation of Camera Calibration Data.

When characterising a digital camera spectrally or colourimetrically, the camera response to a generally diffusely reflecting colour chart is often employed. The recorded responses to the light incident from each colour patch are typically not linearly related to the power of the irradiance on the chart, and the irradiance varies with position on the chart. This necessitates a linearisation of the responses.

Development and validation of a hybrid simulator for ultrasound-guided laparoscopic common bile duct exploration.

Background: Ultrasound-guided laparoscopic common bile duct exploration (LCBDE) is the surgical management of choledocholithiasis. The procedure presents significant benefits to patients but still fails to be generalised because of the complex set of skills it requires. A simulator for ultrasound-guided LCBDE would allow trainee surgeons as well as experienced surgeons who perform this surgery seldomly to practice and gain confidence.

On the Quantification of Visual Texture Complexity.

Complexity is one of the major attributes of the visual perception of texture. However, very little is known about how humans visually interpret texture complexity. A psychophysical experiment was conducted to visually quantify the seven texture attributes of a series of textile fabrics: , , , , , , and .

Beyond Tristimulus Color Vision with Perovskite-Based Multispectral Sensors.

In this study, optical multispectral sensors based on perovskite semiconductors have been proposed, simulated, and characterized. The perovskite material system combined with the 3D vertical integration of the sensor channels allow for realizing sensors with high sensitivities and a high spectral resolution. The sensors can be applied in several emerging areas, including biomedical imaging, surveillance, complex motion planning of autonomous robots or vehicles, artificial intelligence, and agricultural applications.

Optimized light source spectral power distribution for RGB camera based spectral reflectance recovery.

The accuracy of recovered spectra from camera responses mainly depends on the spectral estimation algorithm used, the camera and filters selected, and the light source used to illuminate the object. We present and compare different light source spectrum optimization methods together with different spectral estimation algorithms applied to reflectance recovery. These optimization methods include the Monte Carlo (MC) method, particle swarm optimization (PSO) and multi-population genetic algorithm (MPGA).

Translucency perception: A review.

Translucency is an optical and a perceptual phenomenon that characterizes subsurface light transport through objects and materials. Translucency as an optical property of a material relates to the radiative transfer inside and through this medium, and translucency as a perceptual phenomenon describes the visual sensation experienced by humans when observing a given material under given conditions. The knowledge about the visual mechanisms of the translucency perception remains limited.

Hyperspectral Texture Metrology Based on Joint Probability of Spectral and Spatial Distribution.

Texture characterization from the metrological point of view is addressed in order to establish a physically relevant and directly interpretable feature. In this regard, a generic formulation is proposed to simultaneously capture the spectral and spatial complexity in hyperspectral images. The feature, named relative spectral difference occurrence matrix (RSDOM) is thus constructed in a multireference, multidirectional, and multiscale context.

Colour-Balanced Edge-Guided Digital Inpainting: Applications on Artworks.

The virtual inpainting of artworks provides a nondestructive mode of hypothesis visualization, and it is especially attractive when physical restoration raises too many methodological and ethical concerns. At the same time, in Cultural Heritage applications, the level of details in virtual reconstruction and their accuracy are crucial. We propose an inpainting algorithm that is based on generative adversarial network, with two generators: one for edges and another one for colors.

ZCAM, a colour appearance model based on a high dynamic range uniform colour space.

A colour appearance model based on a uniform colour space is proposed. The proposed colour appearance model, ZCAM, comprises of comparatively simple mathematical equations, and plausibly agrees with the psychophysical phenomenon of colour appearance perception. ZCAM consists of ten colour appearance attributes including brightness, lightness, colourfulness, chroma, hue angle, hue composition, saturation, vividness, blackness, and whiteness.

LED primary selection algorithms for simulation of CIE standard illuminants.

Although mixture of LEDs is being considered as a simulator of the CIE daylight series, the performance of the simulations is highly dependent on the SPD of the selected LEDs. An algorithm for selection of the best LEDs for simulation of the CIE daylight series is helpful in this regard. To address this problem, using 200 imaginary light primaries and 40 real LEDs, three algorithms based on concepts of equally spacing of wavelength range ("Equal"), Gram Schmidt orthogonalization in LEDs/light primaries spectral subspace ("Gram") and the generalization of Gram Schmidt orthogonalization in the LEDs/light primaries projections onto the illuminants subspace ("Ortho") were proposed and studied.

Perovskite Color Detectors: Approaching the Efficiency Limit.

Color image sensing by a smartphone or digital camera employs sensor elements with an array of color filters for capturing basic blue, green, and red color information. However, the normalized optical efficiency of such color filter-based sensor elements is limited to only one-third. Optical detectors based on perovskites are described, which can overcome this limitation.

Evaluation of the Data Quality from a Round-Robin Test of Hyperspectral Imaging Systems.

In this study, the results from a round-robin test of hyperspectral imaging systems are presented and analyzed. Fourteen different pushbroom hyperspectral systems from eight different institutions were used to acquire spectral cubes from the visible, near infra-red and short-wave infra-red regions. Each system was used to acquire a common set of targets under their normal operating conditions with the data calibrated and processed using the standard processing pipeline for each system.

An Evaluation Framework for Spectral Filter Array Cameras to Optimize Skin Diagnosis.

Comparing and selecting an adequate spectral filter array (SFA) camera is application-specific and usually requires extensive prior measurements. An evaluation framework for SFA cameras is proposed and three cameras are tested in the context of skin analysis. The proposed framework does not require application-specific measurements and spectral sensitivities together with the number of bands are the main focus.

A Spectral Filter Array Camera for Clinical Monitoring and Diagnosis: Proof of Concept for Skin Oxygenation Imaging.

The emerging technology of spectral filter array (SFA) cameras has great potential for clinical applications, due to its unique capability for real time spectral imaging, at a reasonable cost. This makes such cameras particularly suitable for quantification of dynamic processes such as skin oxygenation. Skin oxygenation measurements are useful for burn wound healing assessment and as an indicator of patient complications in the operating room.

Multispectral camera as spatio-spectrophotometer under uncontrolled illumination.

Multispectral constancy enables the illuminant invariant representation of multi-spectral data. This article proposes an experimental investigation of multispectral constancy through the use of multispectral camera as a spectrophotometer for the reconstruction of surface reflectance. Three images with varying illuminations are captured and the spectra of material surfaces is reconstructed.

Perceptually Validated Cross-Renderer Analytical BRDF Parameter Remapping.

Material appearance of rendered objects depends on the underlying BRDF implementation used by rendering software packages. A lack of standards to exchange material parameters and data (between tools) means that artists in digital 3D prototyping and design, manually match the appearance of materials to a reference image. Since their effect on rendered output is often non-uniform and counter intuitive, selecting appropriate parameterisations for BRDF models is far from straightforward.

Illuminant estimation in multispectral imaging.

With the advancement in sensor technology, the use of multispectral imaging is gaining wide popularity for computer vision applications. Multispectral imaging is used to achieve better discrimination between the radiance spectra, as compared to the color images. However, it is still sensitive to illumination changes.

Modeling coverage-dependent ink thickness in ink-jet printing.

We propose a simple extension of the Murray-Davis halftone reflectance model that accounts for the change of ink dot reflectance due to ink spreading. Significant improvement of the prediction accuracy is obtained for a range of paper substrates and printer combinations compared to the classical Yule-Nielsen and Clapper-Yule models. The results show that ink dot thickness dependency is the main factor limiting the validity of the Murray-Davis model and that optical dot gain can be neglected when the model is calibrated for one specific printer, ink, and substrate combination.

A sensor-data-based denoising framework for hyperspectral images.

Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values.

Spectrogenic imaging: a novel approach to multispectral imaging in an uncontrolled environment.

Increasing the number of imaging channels beyond the conventional three has been shown to be beneficial for a wide range of applications. However, it is mostly limited to imaging in a controlled environment, where the capture environment (illuminant) is known a priori. We propose here a novel system and methodology for multispectral imaging in an uncontrolled environment.