Fairchild has argued that color spaces are of questionable utility for understanding perception. Here, we go through various concepts of mathematical spaces, ranging from abstract topological spaces to Euclidean ones, and discuss how color stimuli, color matches, and color perceptions can be adequately represented by means of some of these spaces. In particular, we argue that the set of color perceptions can be represented as a metric space that is homeomorphic to a neither open nor closed convex cone in an n -dimensional Banach space of equivalence classes of “generalized metamers.” Finally, for higher color metrics, we sketch how Riemannian geometry can be used to create a unified representation of color stimuli and color perceptions.

The importance of quantifying uncertainty in deep networks has become paramount for reliable real-world applications. In this paper, we propose a method to improve uncertainty estimation in medical Image-to-Image (I2I) translation. Our model integrates aleatoric uncertainty and employs Uncertainty-Aware Regularization (UAR) inspired by simple priors to refine uncertainty estimates and enhance reconstruction quality. We show that by leveraging simple priors on parameters, our approach captures more robust uncertainty maps, effectively refining them to indicate precisely where the network encounters difficulties, while being less affected by noise. Our experiments demonstrate that UAR not only improves translation performance, but also provides better uncertainty estimations, particularly in the presence of noise and artifacts. We validate our approach using two medical imaging datasets, showcasing its effectiveness in maintaining high confidence in familiar regions while accurately identifying areas of uncertainty in novel/ambiguous scenarios.

This study investigates the impact of spectral filtering on color-matching functions (CMFs) and its implications for observer variability modeling. We conducted color matching experiments with a single observer, both with and without a spectral filter in front of a bipartite field. Using a novel computational approach, we estimated the filter transmittance and transformation matrix necessary to convert unfiltered CMFs to filtered CMFs. Statistical analysis revealed good agreement between estimated and measured filter characteristics, particularly in central wavelength regions. Applying this methodology to compare between Stiles and Burch 1955 (SB1955) mean observer CMFs and our previously published "ICVIO" mean observer CMFs, we identified a "yellow" (short-wavelength suppressing) filter that effectively transforms between these datasets. This finding aligns with our hypothesis that observed differences between the CMF sets are attributable to age-related lens yellowing (average observer age: 49 years in ICVIO versus 30 years in SB1955). Our approach enables efficient representation of observer variability through a single filter rather than three separate functions, offering potentially reduced experimental overhead while maintaining accuracy in characterizing individual color vision differences.

As the number of people affected by diseases in the gastrointestinal system is ever-increasing, a higher demand for preventive screening is inevitable. This will significantly increase the workload on gastroenterologists. To help reduce the workload, tools from computer vision may be helpful. In this paper, we investigate the possibility of constructing 3D models of whole sections of the human colon using image sequences from wireless capsule endoscope video, providing improved visualization as well as position localization of pathologies for gastroenterologists. As capsule endoscope images contain distortion and artifacts non-ideal for many 3D reconstruction algorithms, the problem is challenging. However, recent developments of virtual graphics-based models of the human gastrointestinal system, where distortion and artifacts can be enabled or disabled, make it possible to ‘‘dissect’’ the problem. The graphical model also provides a ground truth, enabling computation of geometric distortion introduced by the 3D reconstruction method. In this paper, most distortions and artifacts are first left out to determine if it is feasible to reconstruct whole sections of the human gastrointestinal system by existing methods. We demonstrate that 3D reconstruction is possible through simultaneous localization and mapping. Further, to reconstruct the gastrointestinal wall surface from resulting point clouds, which vary greatly in density, Poisson surface reconstruction is a good option. Noise and artifacts are then enabled to analyze their effect on the 3D reconstruction. The results are promising, encouraging further research and development on the topic.

Accurate characterization of goniochromatic materials, which show angle-dependent color variations, is a challenging task due to their complex optical behavior resulting from diffraction, thin-film interference, and structural coloration. The bidirectional reflectance distribution function (BRDF) is an effective tool for characterizing these materials. In this work, we examine a recently proposed empirical goniochromatic BRDF model and assess its performance for our highly specular and highly goniochromatic samples. Using a few measurements obtained from a handheld goniospectrophotometer, we propose a separation between the near-specular and diffuse components. This modification significantly enhances the original model's performance, enabling more accurate representation and analysis of our goniochromatic materials.

Linear minimum mean square error can be used to demosaic images from a color-polarization filter array (CPFA) sensor. Despite its good performance, the reconstruction produces high-frequency artifacts. An additional refinement step could enable enhancement of both the quantitative and visual quality of the demosaiced image. We propose a complete demosaicing framework by first studying the model selection for linear minimum mean square error using cross-validation techniques and then optimizing the anisotropic diffusion parameters. The results show that the training model converges quickly and that the refinement step enables the reduction of the edge artifacts. We also demonstrate that the proposed demosaicing method performs better compared with a dedicated CPFA demosaicing algorithm in terms of peak signal-to-noise ratio. (c) 2025 SPIE and IS&T

A wireless capsule endoscope (WCE) is a medical device designed for the examination of the human gastrointestinal (GI) tract. Three-dimensional models based on WCE images can assist in diagnostics by effectively detecting pathology. These 3D models provide gastroenterologists with improved visualization, particularly in areas of specific interest. However, the constraints of WCE, such as lack of controllability, and requiring expensive equipment for operation, which is often unavailable, pose significant challenges when it comes to conducting comprehensive experiments aimed at evaluating the quality of 3D reconstruction from WCE images. In this paper, we employ a single-image-based 3D reconstruction method on an artificial colon captured with an endoscope that behaves like WCE. The shape from shading (SFS) algorithm can reconstruct the 3D shape using a single image. Therefore, it has been employed to reconstruct the 3D shapes of the colon images. The camera of the endoscope has also been subjected to comprehensive geometric and radiometric calibration. Experiments are conducted on well-defined primitive objects to assess the method’s robustness and accuracy. This evaluation involves comparing the reconstructed 3D shapes of primitives with ground truth data, quantified through measurements of root-mean-square error and maximum error. Afterward, the same methodology is applied to recover the geometry of the colon. The results demonstrate that our approach is capable of reconstructing the geometry of the colon captured with a camera with an unknown imaging pipeline and significant noise in the images. The same procedure is applied on WCE images for the purpose of 3D reconstruction. Preliminary results are subsequently generated to illustrate the applicability of our method for reconstructing 3D models from WCE images.

Anisotropic diffusion has long been an important tool in image processing. More recently, it has also found its way to colour imaging. Until now, mainly Euclidean colour spaces have been considered in this context, but recent years have seen a renewed interest in and importance of non-Euclidean colour geometry. The main contribution of this paper is the derivation of the equations for anisotropic diffusion in Riemannian colour geometry. It is demonstrated that it contains several well-known solutions such as Perona–Malik diffusion and Tschumperlé–Deriche diffusion as special cases. Furthermore, it is shown how it is non-trivially connected to Sochen’s general framework for low-level vision. The main significance of the method is that it decouples the coordinates used for solving the diffusion equation from the ones that define the metric of the colour manifold, and thus directs the magnitude and direction of the diffusion through the diffusion tensor. It also enables the use of non-Euclidean colour manifolds and metrics for applications such as denoising, inpainting, and demosaicing, based on anisotropic diffusion.

This article presents a compact visual colorimeter for the purpose of measuring color-matching functions (CMFs) of individual observers through psychophysical experiments. Constructed from 3D-printed parts, optical elements, and LED-based light engines, the colorimeter facilitates the juxtaposition of two fields to create a bipartite field. The system underwent characterization to evaluate factors that may impact color-matching experiments, such as LED-light stability, spatial homogeneity of the bipartite field, and potential stray-light leakage. The study aimed to assess the accuracy and performance of the system in measuring individual observer CMFs. Results indicate that the system is stable enough to measure both intra- and inter-observer variations in CMFs.

3D shape reconstruction from images is an active topic in computer vision. Shape-from-Focus (SFF) is an important approach which requires image stack in a focus controlled manner to infer the 3D shape. In this article, 3D reconstruction of synthetic gastrointestinal regions is done using SFF. Image stack is generated in Blender software with focus controlled camera. A color focus measure is applied for shape recovery followed by a weighted L2 regularizer to estimate for inaccurate depth values. A precise comparison is done between recovered shape and ground truth data by measuring the depth error and correlation between them. Results shows that SFF technique will be practical for 3D reconstruction of GI regions with focus and motion controlled pillcams which is technologically feasible to implement.

In colour science, colour matching functions (CMFs) are essential for measuring how sensitive the human eye is to various light wavelengths and determining the colour of stimuli in various viewing situations. It has traditionally taken a lot of time and effort to conduct colour-matching studies to describe an observer’s perception of colour. This article presents a simple and compact 3D-printed colorimeter designed to conduct colour-matching experiments. A pilot study was conducted using the colorimeter with four observers participating in a maximum saturation-type colour matching experiment., where they would match spectral lights in the 400-720 nm range to three narrow band LED primaries. The study aimed to assess the accuracy and performance of the system in measuring individual observer CMFs. Results showed that the CMFs of the four observers showed normal characteristics of a colour-normal observer. However, the limited number of measurements per observer may have contributed to the lack of smoothness in the CMFs. The CMFs of one of the observers were compared with Stiles and Burch 1955 RGB CMFs, after normalising to the same primaries. We noted that the red and green functions fell within the expected range, while the blue function showed some unusual characteristics. The limitations of the colorimeter and overall pilot study were also discussed. In conclusion, the colorimeter showed promising results in measuring CMFs, however the limitations need to be addressed to improve matching accuracy. Additionally, further measurements are required to better characterise intra-observer and inter-observer variabilities.

Since the introduction of the Retinex theory by Land and McCann in 1971, a multitude of different families, versions, interpretations, implementations, and applications have been proposed. The applications for image enhancement mainly differ in (i) how they explore the locality of the images to determine the local context, and (ii) how they recompute the pixel values based on this context. STRESS (spatio-temporal Retinex-inspired envelopes with stochastic sampling) is one of many quite successful members of the family of Retinex-based image enhancement algorithms. It explores the locality using a stochastic sampling technique, resulting in two envelope images - one maximum and one minimum envelope, completely enclosing the image signal and serving as a representation of the local image context. In this paper, we propose to exchange the stochastic sampling technique of STRESS, which causes significant chromatic noise, with an adapted version of constrained linear anisotropic diffusion for computing the envelopes, resulting in almost noise-free images. Using both subjective experiments and objective image metrics, we show that it improves the perceived and measured image quality and reduces noise artefacts. (C) 2023 Society for Imaging Science and Technology.

Observer metamerism (OM) is the name given to the variability between the color matches that individual observers consider accurate. The standard color imaging approach, which uses color-matching functions of a single representative observer, does not accurately represent every individual observer’s perceptual properties. This paper investigates OM in color displays and proposes a quantitative assessment of the OM distribution across the chromaticity diagram. An OM metric is calculated from a database of individual LMS cone fundamentals and the spectral power distributions of the display’s primaries. Additionally, a visualization method is suggested to map the distribution of OM across the display’s color gamut. Through numerical assessment of OM using two distinct publicly available sets of individual observers’ functions, the influence of the selected dataset on the intensity and distribution of OM has been underscored. The case study of digital cinema has been investigated, specifically the transition from xenon-arc to laser projectors. The resulting heatmaps represent the “topography” of OM for both types of projectors. The paper also presents color difference values, showing that achromatic highlights could be particularly prone to disagreements between observers in laser-based cinema theaters. Overall, this study provides valuable resources for display manufacturers and researchers, offering insights into observer metamerism and facilitating the development of improved display technologies.

Measuring the optical properties of highly diffuse materials is a challenge as it could be related to the white colour or an oversaturation of pixels in the acquisition system. We used a spatially resolved method and adapted a nonlinear trust-region algorithm to the fit Farrell diffusion theory model. We established an inversion method to estimate two optical properties of a material through a single reflectance measurement: the absorption and the reduced scattering coefficient. We demonstrate the validity of our method by comparing results obtained on milk samples, with a good fitting and a retrieval of linear correlations with the fat content, given by R2 scores over 0.94 with low p-values. The values of absorption coefficients retrieved vary between 1 × 10−3 and 8 × 10−3 mm−1, whilst the values of the scattering coefficients obtained from our method are between 3 and 8 mm−1 depending on the percentage of fat in the milk sample, and under the assumption of the anisotropy factor g>0.8. We also measured and analyzed the results on white paint and paper, although the paper results were difficult to relate to indicators. Thus, the method designed works for highly diffuse isotropic materials.

Capsule endoscopy is about to become an alternative to traditional colonoscopy. One uses a wireless camera to visualize the gastrointestinal (GI) tract. A 3D model based on image sequences obtained from wireless capsule endoscopy (WCE) can be helpful to diagnose or analyse areas of interests. We have therefore investigated the possibility to provide enhanced viewing for gastroenterologists by reconstructing 3D shapes from WCE images. The study is done on virtual graphics-based models of human GI regions. The shape from shading (SFS) method is applied to colon images and the quality of the reconstructed shapes is compared with ground truth models. WCE images suffer from uneven and dim illumination due to point light source. Therefore, we provide a method based on surface normals from reconstructed 3D models to enhance contrast particularity in images capturing larger depths by changing the illumination from point light to directional light. Images of different resolution are also tested to evaluate their effect on the quality of the 3D reconstruction. We have also tested the shape from focus (SFF) method, a possibility for future WCEs, and compared the results with SFS. Finally, enhanced images and 3D shapes recovered with both methods have been evaluated by gastroenterologists through subjective experiments. Objective experiments indicate that both methods are capable of reconstructing the 3D shapes of colon images successfully, but the SFF method is better at retaining details in the reconstructed models than the SFS method. Subjective experiments show that contrast enhanced images are highly preferred over original images. Also, having the reconstructed 3D models in addition to the images during evaluation is found to be very useful by gastroenterologists and sometimes even being preferred over the original image.

The variety of spectral imaging systems makes the portability of imaging solutions and the generalization of research difficult. We advocate for the creation of a standard representation space for spectral imaging. We propose a space that allows connection to colorimetric standards and to spectral reflectance factors, while keeping a low and practical dimension. The performance of one instance of this standard is evaluated through simulations. Results demonstrate that this space may show reduced performance in accuracy than some native camera spaces, especially instances with a number of bands larger than the standardized dimension, but this limitation comes with benefit in size and standardization.

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. We present a new single image colour chart-based estimation method of responses, that are linearly related to camera response values known as ground truth. The method estimates the spatial geometry of the irradiance incident on the chart attenuated by lens vignetting and compensates individually for volumetric and per colour channel non-linearities, including compensation for physical scene and camera properties in a pipeline of successive signal transformations between the estimated linear and the given recorded responses. The estimation is controlled by introducing a novel Additivity Principle of linear responses, which is derived from the spectral reflectances of the coloured surfaces on the colour chart, observing that linear relations of the spectral reflectances are equal to the relations of the corresponding linear responses. Crucially, the additivity principle is not subject to metamerism. The method is fundamentally solely reliant on a one-shot set of one triplet of response values sampled from each patch of a colour chart with known spectral reflectances, where rendition level, gray scale, illuminant, camera sensor curves, irradiance geometry, vignetting, moderate specular reflection, colour space, colour correction, gamut correction and noise level are unknown.