Adaptive auditory brightness perception

Perception adapts to the properties of prior stimulation, as illustrated by phenomena such as visual color constancy or speech context effects. In the auditory domain, only little is known about adaptive processes when it comes to the attribute of auditory brightness. Here, we report an experiment that tests whether listeners adapt to spectral colorations imposed on naturalistic music and speech excerpts. Our results indicate consistent contrastive adaptation of auditory brightness judgments on a trial-by-trial basis. The pattern of results suggests that these effects tend to grow with an increase in the duration of the adaptor context but level off after around 8 trials of 2 s duration. A simple model of the response criterion yields a correlation of r = .97 with the measured data and corroborates the notion that brightness perception adapts on timescales that fall in the range of auditory short-term memory. Effects turn out to be similar for spectral filtering based on linear spectral filter slopes and filtering based on a measured transfer function from a commercially available hearing device. Overall, our findings demonstrate the adaptivity of auditory brightness perception under realistic acoustical conditions.

Real World Metamer Sets: Or How we Came to Love Noise

It is well known that color formation acts as a noise-reducing lossy compression mechanism that results in ambiguity, known as metamerism. Surfaces that match under one set of conditions-an illuminant and observer or capture device-can mismatch under others. The phenomenon has been studied extensively in the past, leading to important results like metamer mismatch volumes, color correction, reflectance estimation and the computation of metamer sets-sets of all possible reflectances that could result in a given sensor response. However, most of these approaches have three limitations: first, they simplify the problem and make assumptions about what reflectances can look like (i.e., being smooth, natural, residing in a subspace based on some measured data), second, they deal with strict mathematical metamerism and overlook noise or precision, and third, only isolated responses are considered without taking the context of a response into account. In this paper we address these limitations by outlining an approach that allows for the robust computation of approximate unconstrained metamer sets and exact unconstrained paramer sets. The notion of spatial or relational paramer sets that take neighboring responses into account, and applications to illuminant estimation and color constancy are also briefly discussed.

Illuminant Estimation Using Adaptive Neuro-Fuzzy Inference System

Computational color constancy (CCC) is a fundamental prerequisite for many computer vision tasks. The key of CCC is to estimate illuminant color so that the image of a scene under varying illumination can be normalized to an image under the canonical illumination. As a type of solution, combination algorithms generally try to reach better illuminant estimation by weighting other unitary algorithms for a given image. However, due to the diversity of image features, applying the same weighting combination strategy to different images might result in unsound illuminant estimation. To address this problem, this study provides an effective option. A two-step strategy is first employed to cluster the training images, then for each cluster, ANFIS (adaptive neuro-network fuzzy inference system) models are effectively trained to map image features to illuminant color. While giving a test image, the fuzzy weights measuring what degrees the image belonging to each cluster are calculated, thus a reliable illuminant estimation will be obtained by weighting all ANFIS predictions. The proposed method allows illuminant estimation to be dynamic combinations of initial illumination estimates from some unitary algorithms, relying on the powerful learning and reasoning capabilities of ANFIS. Extensive experiments on typical benchmark datasets demonstrate the effectiveness of the proposed approach. In addition, although there is an initial observation that some learning-based methods outperform even the most carefully designed and tested combinations of statistical and fuzzy inference systems, the proposed method is good practice for illuminant estimation considering fuzzy inference eases to implement in imaging signal processors with if-then rules and low computation efforts.

Design of the Poster Image System Based on Human Vision

At present, the human visual perception system is the most effective, accurate, and fast image processing system in the world. This is because human eyes have some special visual features, but the features closely related to image enhancement include color constancy and brightness constancy. This paper presents a new image enhancement framework and computational model which can better simulate human visual features. It is based on the analysis of color constancy and luminance constancy and Retinex theory. And, this is a new image enhancement method in the compressed domain based on Retinex theory. In Retinex theory, DCT coefficients consist of incident components (DC coefficients) and reflection components (AC coefficients). By adjusting the dynamic range of DC coefficients, carefully adjusting AC coefficients, and using the threshold method for block suppression, the compressed domain image can be enhanced. On the basis of Retinex theory, the incident light and reflected light components are considered synthetically, the dynamic range (DC coefficient) of the incident light component and the details of the reflected light component (AC coefficient) are adjusted, and then the incident light component is reexamined. Moreover, it achieves a better image enhancement effect and avoids the blocking effect.

Three-Color Balancing for Color Constancy Correction

This paper presents a three-color balance adjustment for color constancy correction. White balancing is a typical adjustment for color constancy in an image, but there are still lighting effects on colors other than white. Cheng et al. proposed multi-color balancing to improve the performance of white balancing by mapping multiple target colors into corresponding ground truth colors. However, there are still three problems that have not been discussed: choosing the number of target colors, selecting target colors, and minimizing error which causes computational complexity to increase. In this paper, we first discuss the number of target colors for multi-color balancing. From our observation, when the number of target colors is greater than or equal to three, the best performance of multi-color balancing in each number of target colors is almost the same regardless of the number of target colors, and it is superior to that of white balancing. Moreover, if the number of target colors is three, multi-color balancing can be performed without any error minimization. Accordingly, we propose three-color balancing. In addition, the combination of three target colors is discussed to achieve color constancy correction. In an experiment, the proposed method not only outperforms white balancing but also has almost the same performance as Cheng’s method with 24 target colors.

UV Activated Copolymerization Coatings of Urethane Acrylates for Use in the Cosmetic Industry

In the dissertation compositions of urethane diacrylates and monoacrylates have been studied, which when curing under the conditions of UV-activated copolymerization process meeting the requirements of cosmetic varnishes, form cross-linked structure coatings with high strength-deformation, surface hardness, surface light reflectance, adhesion and other parameters. The review of the literature summarizes information on the types of natural nail coatings and the basic components entering them. Restrictions on the choice of basic components entering the system are described. The effect of conditions and components on the natural nail is described. The materials used in the research are described in the methodological part of the work. The process of obtaining compositions is described. The research methods used are described: characterization of rheological properties of non-polymerized compositions, differential thermal analysis of polymerization process, determination of polymerization depth, determination of crosslinked part of polymerized systems, determination of yield tensile strength-deformation, coating surface hardness, surface gloss and surface wear, assessment of adhesion and its durability, in-vitro and in-vivo coating adhesion studies on natural nails, spectroscopic analysis of pigmented coatings and assessment of color constancy, comparison of coating compositions in terms of their functionality and effects on human health. In the experimental part of the work, methodologies for component selection, composite system formation and obtaining appropriate coatings have been developed. A methodology has been developed for the evaluation of the set of structures and properties of the obtained coatings. The influence of the chemical nature and content ratios of urethane diacrylates and monoacrylates suitable for the formation of separate cosmetic coatings on the indicators of cross-linked structures formed in the process of UV-activated copolymerization and the corresponding indicators of coating properties has been studied. The influence of individual additives on the properties of cross-linked coatings, their adhesion to the surface and the durability of the coating at removal process has been evaluated.