Color Consistency Research Articles

Classification of papillary thyroid carcinoma histological images based on deep learning

Papillary thyroid carcinoma (PTC) is a common carcinoma in thyroid. As many benign thyroid nodules have the papillary structure which could easily be confused with PTC in morphology. Thus, pathologists have to take a lot of time on differential diagnosis of PTC besides personal diagnostic experience and there is no doubt that it is subjective and difficult to obtain consistency among observers. To address this issue, we applied deep learning to the differential diagnosis of PTC and proposed a histological image classification method for PTC based on the Inception Residual convolutional neural network (IRCNN) and support vector machine (SVM). First, in order to expand the dataset and solve the problem of histological image color inconsistency, a pre-processing module was constructed that included color transfer and mirror transform. Then, to alleviate overfitting of the deep learning model, we optimized the convolution neural network by combining Inception Network and Residual Network to extract image features. Finally, the SVM was trained via image features extracted by IRCNN to perform the classification task. Experimental results show effectiveness of the proposed method in the classification of PTC histological images.

Enblending Mosaicked Remote Sensing Images With Spatiotemporal Fusion of Convolutional Neural Networks

Mosaicking of remote sensing images stitches images of different moments or sensors to produce a new image under a uniform geographic coordinate system. In a mosaicking process, the critical enblending operation is divided into color balance, seamline finder, and fusion of overlapping areas, which is still challenging to maintain color consistency and data fidelity. In this article, a new mosaicking framework using spatiotemporal fusion is proposed to solve the enblending issue. Two additional low-resolution reference images are introduced for each mosaicking image. With spatiotemporal fusion methods, all mosaicking images are reconstructed to a uniform time, then the combination of overlapping areas become easy. Furthermore, a new spatiotemporal fusion method is proposed by cascading enhanced deep neural networks to fuse images quickly and effectively. In the validation procedure, the proposed method is compared with eight color harmony methods or tools by mosaicking the red, green, and blue bands of Landsat-8 images with images from the moderate-resolution imaging spectroradiometer as the reference. The digital evaluations and visual comparisons demonstrate that the newly method outweighs majority methods regarding to the radiometric, structural, and spectral fidelity, which proves the feasibility of our new enblending method.

Color durability of pigmented slurry surfacing after artificial aging tests simulating weathering and traffic

In the new vision of complete street, the use of colored pavements has been promoted in recent years to improve road user safety and to enhance the reorganization and aesthetic of the urban environment. But, besides several benefits these pavements undergo environmentally and traffic induced changes in appearance, faster than the traditional ones, a few months after installation. Thus, the laboratory-scale investigation analyzed the color durability of pigmented slurry seals, which were prepared using a clear synthetic emulsion and mineral pigments, subject to different artificial accelerated aging procedures. They simulated the exposition to sunlight at high temperature (QUV weathering tester), the aggression of chemical products (salt brine bath) used for winter maintenance operations and the dynamic actions of vehicle tires (loaded wheel tester). The analyses of color change measured with a spectrophotometer highlighted the extreme sensitivity of pigmented thin surfacing to physical and mechanical stresses. Specifically, the thermal and photo-oxidation of the binder film induced by the UV exposure at high temperature and its wear caused by the dynamic passage of rubber tire produced a large supra-threshold color difference on the samples’ surface. These results suggest how a correct mix-design, both in the materials choice and ingredients dosage, should be properly calibrated on the basis of the pavement end-use and of the prevailing climatic conditions to ensure color consistency throughout the pavement lifetime.

Color Correction for Immersive Video Applications

In this paper, the color correction method developed for immersive video systems is presented. The proposed method significantly increases the consistency of color characteristics of multiview sequences, understood both as the temporal and the inter-view consistency, what highly improves the subjective quality of the synthesized virtual views presented to the final user of the immersive video system. Moreover, the proposal allows to significantly increase the quality of the depth maps calculated for natural sequences, e.g., for views with colors inconsistent due to different lighting conditions. It enables more efficient compression of natural multiview video, as the newest encoding standards highly depend on the quality of depth maps. In order to evaluate the performance of the proposal, three experiments were conducted. In the first one, the proposal was compared to state of the art in the typical immersive video application – color correction of a natural multiview sequence. In the second experiment, the performance of the proposal was tested on the Middlebury stereo dataset. In both experiments, the quality of synthesized virtual views was assessed subjectively by a group of 70 naive viewers. The third experiment assessed the influence of color correction on the quality of estimated depth maps. All the experiments showed that the proposal significantly increases the color consistency of the multiview content. Due to the high usefulness and robustness, the proposed color correction method became the MPEG reference software for color correction. The implementation of the method is available for other researchers on the public repository.

A content‐dependent Daltonization algorithm for colour vision deficiencies based on lightness and chroma information

To help CVD (colour vision deficiency) observers distinguish among different colours in digital images, this study proposes a content-dependent Daltonization algorithm based on lightness and chroma information. This improves the trade-offs in contrast, naturalness, and colour consistency deficiencies found in existing methods. Chroma remapping and brightness adjustments on image content are utilized to increase contrast and maximize the preservation of the original hue. In a quantitative study, the proposed method proved more useful for dichromats than did existing methods. The evaluation by research subjects showed that the method was superior to the current methods in balancing contrast, naturalness, and colour consistency.

Unsupervised Haze Removal for High-Resolution Optical Remote-Sensing Images Based on Improved Generative Adversarial Networks

One major limitation of remote-sensing images is bad weather conditions, such as haze. Haze significantly reduces the accuracy of satellite image interpretation. To solve this problem, this paper proposes a novel unsupervised method to remove haze from high-resolution optical remote-sensing images. The proposed method, based on cycle generative adversarial networks, is called the edge-sharpening cycle-consistent adversarial network (ES-CCGAN). Most importantly, unlike existing methods, this approach does not require prior information; the training data are unsupervised, which mitigates the pressure of preparing the training data set. To enhance the ability to extract ground-object information, the generative network replaces a residual neural network (ResNet) with a dense convolutional network (DenseNet). The edge-sharpening loss function of the deep-learning model is designed to recover clear ground-object edges and obtain more detailed information from hazy images. In the high-frequency information extraction model, this study re-trained the Visual Geometry Group (VGG) network using remote-sensing images. Experimental results reveal that the proposed method can recover different kinds of scenes from hazy images successfully and obtain excellent color consistency. Moreover, the ability of the proposed method to obtain clear edges and rich texture feature information makes it superior to the existing methods.

Multi-Camera Color Correction via Hybrid Histogram Matching

With the explosive popularity of multi-camera systems, a challenging problem is how to guarantee the inter-camera color consistency. In this paper, we have developed a hybrid histogram matching (HHM) algorithm that leverages the cumulative color histogram to fulfill this purpose, in which it mainly includes the global color mapping, and local color straightening for uniform color presentation across cameras. Our approach is applicable to any camera pair with sufficient viewing angle overlap, and can be easily extended to support multi-camera setup by pairwisely color map transfer. This HHM method has provided the superior efficiency for color correction when compared with the state-of-the-art algorithms, both objectively and subjectively, via extensive validations on different multi-camera systems. Additional ablation studies have been performed to further examine the capacity of our algorithm in practical applications. We would like to make all materials publicly accessible at https://njuvision.github.io/HHM/ for reproducible research.

Color Rendering in Medical Extended-Reality Applications.

Cross-platform development of medical applications in extended-reality (XR) head-mounted displays (HMDs) often relies on game engines with rendering capabilities currently not standardized in the context of medical visualizations. Many aspects of the visualization pipeline including the characterization of color have yet to be consistently defined across rendering models and platforms. We examined the transfer of color properties from digital objects, through the rendering and image processing steps, to the RGB values sent to the display device. Five rendering pipeline configurations within the Unity engine were evaluated using 24 digital color patches. In the second experiment, the same configurations were evaluated with a tissue slide sample image. Measurements of the change in color associated with each configuration were characterized using the CIE 1976 color difference ([Formula: see text]). We found that the distribution of [Formula: see text]for the first experiment ranges from zero, as in the case using an Unlit Shader, to 25.97, as in the case using default configurations. The default Unity configuration consistently returned the highest [Formula: see text]across all 24 colors and also the largest range of color differences. In the second experiment, [Formula: see text]E ranged from 7.49 to 34.18. The Unlit configuration resulted in the highest [Formula: see text]in three of four selected pixels in the tissue sample image. Changes in color image properties associated with texture import settings were then evaluated in a third experiment using the TG18-QC test pattern. Differences in pixel values were found in all nine of the investigated texture import settings. The findings provide an initial characterization of color transfer and a basis for future work on standardization, consistency, and optimization of color in medical XR applications.

Revisiting print-attribute optimization: a direct pattern generation approach

The properties of prints are not fully determined by the materials they are composed of and the method that was used to compose them. These merely set limits to what a print's properties, such as its colors, sharpness, smoothness, color inconstancy and level of ink use, will be and it is the role of a printing system's imaging pipeline to select a particular combination. Conventionally such choices are implicit in how resources for a pipeline are built and can be improved with experience and trial an error. Performance can be improved though by optimizing for specific attributes, as was previously shown for color consistency, ink use and grain among others. A key constraint that remains here is that optimization is performed on the basis of sampling and search strategies, which have inherent limitations. This paper presents a direct, analytical approach to optimization that hinges on the insight that it can be performed in a convex space even when the properties involved in the optimization do not relate to each other in a convex way. The result both improves performance versus previous methods and does so in considerably less time.

Longitudinal consistency of synesthetic colors for 300 graphemes

Longitudinal consistency of synesthetic colors for 300 graphemes

Jointly optimizing global and local color consistency for multiple image mosaicking

In multiple image mosaicking, color inconsistency is a common and severe problem that degrades the quality of composite images. To avoid the appearance of visible seams, we need to optimize the color consistency before mosaicking multiple images. To facilitate the global optimization framework, existing approaches mainly use less flexible global models, e.g., the linear or gamma model, to eliminate the color differences between multiple images. These models can effectively ensure that the global tones in multiple images are consistent. However, their ability to correct local color discrepancies is usually poor. In this paper, we propose a novel image color correction approach that can correct global and local color discrepancies simultaneously and preserve image gradient as much as possible. First, we design an effective and flexible color correction model to represent the color mapping function for each image. Instead of using the same global model to correct color discrepancies for all pixels in one image, we apply a series of local linear models for color correction. For different superpixel regions, different linear models are applied to model the mapping functions. Second, based on this model, a specific global cost function that considers both gradient preservation and color consistency is designed and solved. In addition, a global color constraint is fused into this cost function to ensure that the corrected images have the similar global tone. Thus, we can jointly optimize the global and local color consistency by minimizing this cost function. The experimental results on several challenging datasets captured by different sensors demonstrate that the proposed approach outperforms the state-of-the-art color correction approaches in both visual quality and quantitative metrics.

DICOM Format and Protocol Standardization-A Core Requirement for Digital Pathology Success.

As the use of digital techniques in toxicologic pathology expands, challenges of scalability and interoperability come to the fore. Proprietary formats and closed single-vendor platforms prevail but depend on the availability and maintenance of multiformat conversion libraries. Expedient for small deployments, this is not sustainable at an industrial scale. Primarily known as a standard for radiology, the Digital Imaging and Communications in Medicine (DICOM) standard has been evolving to support other specialties since its inception, to become the single ubiquitous standard throughout medical imaging. The adoption of DICOM for whole slide imaging (WSI) has been sluggish. Prospects for widespread commercially viable clinical use of digital pathology change the incentives. Connectathons using DICOM have demonstrated its feasibility for WSI and virtual microscopy. Adoption of DICOM for digital and computational pathology will allow the reuse of enterprise-wide infrastructure for storage, security, and business continuity. The DICOM embedded metadata allows detached files to remain useful. Bright-field and multichannel fluorescence, Z-stacks, cytology, and sparse and fully tiled encoding are supported. External terminologies and standard compression schemes are supported. Color consistency is defined using International Color Consortium profiles. The DICOM files can be dual personality Tagged Image File Format (TIFF) for legacy support. Annotations for computational pathology results can be encoded.

Positive calretinin stain with immunohistochemistry in a 49 year-old female with cardiac myxoma: A case report

Background: Primary tumors of the heart are scarce. Cardiac myxoma is a primary benign heart tumor most often found with an incidence of 0.5-1.0 cases per million population per year and 90% diagnosed in the fourth to seventh decades of life, rarely found in children. Cardiac myxoma is three times more common in women than in men. These tumors are mostly found in the left atrium.Case description: Female, a 49-year-old patient, came with palpitations, shortness of breath, and weakness since the previous six months. On echocardiography, found a mass in the left atrium suspected of a left atrial myxoma. Surgery was performed, and the specimen was sent for histopathological examination. Macroscopically, the tumor mass shows an irregular shape, brownish color, and spongy consistency. Microscopic examination shows the tumor consisting of proliferation of spindle-shaped and stellate cells, with oval to round nuclei, eosinophilic cytoplasm, mostly scattered, some of which are arranged cord and nest, infiltrative between the myxoid stroma and partially surround small blood vessels to form a vasoformative ring. The specimen also contains the proliferation of blood vessels, extravasation of erythrocytes, and the distribution of inflammatory cells and hemosiderophages. The result of the immunohistochemical examination with calretinin was positive.Conclusion: This case was concluded as cardiac myxoma based on clinical features, echocardiography, macroscopic, routine histopathological, and immunohistochemical examinations.

The main results of work on the selection of gourds in the Volgograd Trans-Volga region

Relevance. One of the main methods for solving the problem of providing the population of the Russian Federation with vegetable and melon products is the development of selection and seed production. The creation of new competitive varieties and hybrids will enable the vegetable industry to transfer to a qualitatively new level of development.Material and methods.The object of research is new varieties and hybrids of watermelon, melon and pumpkin, created at the Bykov experimental station in the rainfed conditions of the Volgograd TransVolga region. Methods of creation are intervarietal and interlinear hybridization. Results and conclusions.As a result of breeding work at the station, a number of varieties and heterosis hybrids of melons and gourds were created, which significantly expanded the assortment of the melon breeding industry. Over the past 5 years, 4 varieties of watermelon, 2 heterotic hybrids of watermelon, 3 varieties of melon and 1 grade of pumpkin have been included in the State Register of Breeding Achievements. The assortment of new varieties varies in terms of ripening, dry matter content, shape and color of the fruit background, as well as in color and pulp consistency. The length of the growing season of the created varieties and hybrids of watermelon ranges from 63 days in early ripening (Duet F1, Temp F1, Meteor) to 85 in the mid-ripening variety Malachite. The highest solids content of the new variety of watermelon Medunok is up to 14%. Among melon varieties, the shortest growing season is characterized by the Comet variety up to 70 days. All varieties have a high solids content of 14.0-19.0% and a thick flesh. Promising pumpkin varieties are distinguished by a bright coloration of the pulp, a high carotene content and a long storage period. Thus, the introduction of new varieties of gourds in commodity and home garden melon farming will allow the conveyor growing of products, increase the product mix and the period of consumption of fresh produce.

Avaliação sensorial de ketchup adicionado de amido de semente de pitomba

O ketchup é um molho popular em diversos países, caracterizado pela cor forte, sabor adocicado e consistência espessa. Variações nessas características podem interferir na aceitação do produto, assim, objetivou-se com este estudo analisar a aceitação dos parâmetros sensoriais (aroma, cor, sabor, aparência) e intenção de compra de ketchup adicionado de amido de pitomba e com isso comparar com os atributos sensoriais de ketchup adicionado de amido de milho comercial. A extração do amido foi realizada por trituração da semente da pitomba em solução de metabissulfito de sódio (0,2%) seguida de secagem à 50 °C. Os ketchups foram formulados com adição de 0,5 e 1% de amido de pitomba, 0,5 e 1% de amido de milho, e uma formulação controle. As formulações foram avaliadas microbiologicamente quanto coliformes termotolerantes e Salmonella e submetidos a avaliação de aceitação sensorial quanto aos parâmetros de cor, aparência, aroma, sabor e intenção de compra. Os resultados revelaram que as formulações apresentaram bom padrão microbiológico e os ketchups não apresentaram diferença significativa (p ≤ 0,05) entre os parâmetros de cor, aparência, aroma e sabor, indicando que as porcentagens e os tipos de amido utilizado não causaram interferência nas características sensoriais avaliadas. As maiores intenções de compra foram registradas para as formulações adicionadas de amidos, sugerindo a preferência dos consumidores por formulações consistentes.

Practical Camera Sensor Spectral Response and Uncertainty Estimation.

Knowledge of the spectral response of a camera is important in many applications such as illumination estimation, spectrum estimation in multi-spectral camera systems, and color consistency correction for computer vision. We present a practical method for estimating the camera sensor spectral response and uncertainty, consisting of an imaging method and an algorithm. We use only 15 images (four diffraction images and 11 images of color patches of known spectra to obtain high-resolution spectral response estimates) and obtain uncertainty estimates by training an ensemble of response estimation models. The algorithm does not assume any strict priors that would limit the possible spectral response estimates and is thus applicable to any camera sensor, at least in the visible range. The estimates have low errors for estimating color channel values from known spectra, and are consistent with previously reported spectral response estimates.

HIGH-RESOLUTION OPTICAL SATELLITE IMAGES COLOR CONSISTENCY METHOD BASED ON EXTERNAL COLOR REFERENCES

Abstract. Affected by factors such as season, illumination, atmospheric and sensor distortion, different satellite images often show obvious color difference, resulting in “stitching seams” at the edge of adjacent images, which seriously affects the application of satellite images. This study proposes a novel color consistency method for optical satellite images utilizing external color reference. Firstly, we improved the dark channel defogging method combining with the atmospheric distribution characteristics of satellite images, and used it to perform atmospheric correction on satellite images; Secondly, we corrected the color of atmospheric corrected satellite images through low-frequency signal replacement. Finally, we use a linear model to establish the relationship between high and low frequency signals, and stretching the high-frequency signal of images through local modelling. We selected two sets of representative experimental data for experiments, both the visual and quantitative obtained excellent results.

Deep frying cooking oils promote the high risk of metastases in the breast-A critical review

Deep-frying is the most common food preparation method, manifestations of color, taste, flavor, and fried consistency. The beneficial role of vegetable oils become deteriorate when repeatedly treated with higher temperature and air. Repeatedly heated cooking oils (RCO) produce various byproducts, containing polycyclic aromatic hydrocarbons (PAHs) and aldehydes, well-known to be a carcinogenic, mutagenic, and tumorigenic properties. RCO is nowadays one of the often consumed media for cooking and frying, which intake can cause various unhealthy adverse effects including various cancer in the multiple organs. Hence, the present comprehensive study targets to provide the intake of RCO elevate the risks of human breast cancer. The data on RCO and its impacts were obtained via various electronic findings and library databases. Notable studies have confirmed that the effects of RCO have been attributed to their unfavorable effects, and underlying molecular mechanisms can also strongly promoting tumorigenic effects in the mammary organ.

Grid Model-Based Global Color Correction for Multiple Image Mosaicking

Color consistency optimization for multiple images is a challenging problem in image mosaicking. To facilitate the global color optimization, existing approaches mainly use less flexible models, e.g., linear or gamma function, to eliminate the color differences between multiple images. However, these models often struggle to eliminate the color differences that existed in the local areas and preserve the image gradient information. To solve this problem, we creatively propose a novel color-correction model, which comprised a series of local grid linear models. This model is simple, but it is flexible enough to approximate a variety of complicated local color variations. To obtain the optimal model parameters for each image globally, a specific cost function that considers both color consistency and gradient preservation is designed and solved. The aim of our approach is to generate a composite image with visually consistent color. The original color information may be destroyed. Thus, this approach is unsuitable for the quantitative remote sensing applications. The experimental results on several challenging data sets show that the proposed approach outperforms state-of-the-art approaches in both visual quality and quantitative metrics.

Recovering figure‐ground perception in Tehran's color plan

AbstractTehran's color plan was carried out during 1990s with the primary purpose of restoring color consistency particularly to the historic center of the city. In fact, it attempted to bring unity and avoid color pollution to the cityscape. However, it seems to have been neglectful of many other factors, including orientation, legibility, and the mental image of the city. Further analysis shows that it fails to address figure‐ground perception, as a sign of hierarchy and order, on the urban scale. Hence, this article aims to recover figure‐ground perception with respect to Brandi's theory of restoration as well as the constituent elements of the image of the city. The study makes a contribution to the field of urban design/planning, as it offers important insights into a critical aspect of city color plan and cityscape.