Original Color Research Articles

Generation (not production) improves the fidelity of visual representations in picture naming.

The production effect refers to the finding that participants better remember items read aloud than items read silently. This pattern has been attributed to aloud items being relatively more distinctive in memory than silent items, owing to the integration of additional sensorimotor features within the encoding episode that are thought to facilitate performance at test. Other theorists have instead argued that producing an item encourages additional forms of processing not limited to production itself. We tested this hypothesis using a modified production task where participants named monochromatic line drawings aloud or silently either by generating the names themselves (no label condition) or reading a provided label (label condition). During a later test, participants were presented with each line drawing a second time and required to reproduce the original color and location using a continuous slider. Production was found to improve memory for visual features, but only when participants were required to generate the label themselves. Our findings support the notion that picture naming improves memory for visual features; however, this benefit appears to be driven by factors related to response generation rather than production itself.

A novel carboxymethyl cellulose/gum xanthan and citric acid-based film that enhances the precision of blackcurrant anthocyanin-induced color detection for beef spoilage tracking

Leveraging blackcurrant anthocyanin (BC) as an indicator and carboxymethyl cellulose (CMC), gum xanthan (GX), and citric acid (CA) as film fabricating materials, an innovative amine-responsive beef freshness intelligent film, known as CGC-BC, was successfully created. It was found that the physical characteristics, sensitivity to the biogenic amine reaction, and original color of the film were all highly influenced by the pH of the film-forming solutions. The film's freshness monitoring ability was assessed at 4, 25, and 35 °C, and various color changes were employed to monitor beef deterioration. ΔE values and the visual color difference of the low-concentration (SCG-BC-0.08 and SCG-BC-0.16) ammonia-sensitive indicator films demonstrated significant color changes than the high-concentration (SCG-BC-0.24 and SCG-BC-0.32) films. The films biodegradation (37.16 to 51.49%) ability was enhanced with increase in the proportions of BC. As the TVB-N and pH values of beef increased with the different temperatures and time and different color changes were observed from red to pink, black to brown, and yellow.

Donor‐Acceptor‐Based Conjugated Fluorescent Probes for Volatile Acid Detection

AbstractStimuli‐responsive materials based on π‐conjugated donor‐acceptor systems have great potential for sensing applications in solution and solid state. The photophysical properties of an oligo(p‐phenylenevinylene) series consisting of five push‐pull type molecules were systematically investigated to switch their absorption and emission properties by using trifluoroacetic acid as a specific external analyte. During the trifluoracetic acid sensing, the terminal pyridine units of the molecules undergo the protonation and lead to the broader absorption band at a longer wavelength region owing to the π‐π* characteristics of molecules. Upon exposing solid samples to the trifluoracetic acid vapors, the initial color of solid samples changed from yellow to orange for three‐ring system‐based molecules and brick red to wine red color for five‐ring system‐based molecules with the shifting of emission band to the longer wavelength region. Furthermore, exposing the trifluoracetic acid‐fumed solid samples to triethylamine vapors, the color of the solid samples reverted to their original colors and emission properties. The DFT analysis indicated a decreased energy band gap for the protonated molecules compared to the neutral molecules, suggesting a redshift in both the absorption and emission spectra of the protonated molecules. Thus, all the molecules of an Oligo(p‐phenylenevinylene) series can be utilized effectively for volatile acid detection.

Multimodal anti-counterfeiting and optical storage application based on luminescence reversible modification and color change of photochromic phosphor

Reversible upconversion luminescence (RUCL) modification based on photochromism has received considerable interest due to its potential applications in optical storage and invisible optical anti-counterfeiting. Herein, white β-Ba2ScAlO5: Yb3+, Er3+ (β-BSAO-YE) phosphor was irradiated with 254 nm light, which caused the phosphor to turn blue due to the increase of oxygen vacancy. The blue β-BSAO-YE phosphor returns to its original color upon stimulation with 808 nm laser light or 125 °C, exhibiting a double photo-induced reversible photochromic change. The green and red upconversion luminescence (UCL) of the β-BSAO-YE were reversibly modified according to their photochromic properties. The UCL modification changes the luminescence color of the pattern, indicating that β-BSAO-YE phosphor is an ideal compound anti-counterfeit agent. The light information recorded on the β-BSAO-YE binary photochromic dot matrix can be read under ultraviolet (UV) and near-infrared (NIR) excitation, demonstrating the potential application of β-BSAO-YE phosphors as optical data storage media. In addition, the cyclic experiment showed good photochromic and UCL modulation repeatability. The new luminescent β-BSAO-YE not only proposes a new way to exploring upconversion red light materials, but also provides new materials for optical storage, optical information and optical anti-counterfeiting.

Chitosan/agarose hydrogel dressing: pH response real-time monitoring and chemo-/photodynamic therapy synergistic treatment of infected wounds

The early diagnosis and real-time monitoring of bacterial infections are of great significance for the establishment of integrated diagnosis and treatment systems. In this study, a pH-responsive smart hydrogel patch system, named CABP, was developed to monitor and treat wound infections. CABP has a sandwich structure, with non-woven fabric/chitosan (NF/CS) as the intermediate skeleton layer, Agarose/chitosan/Bromothymol Blue (AG/CS/BTB) hydrogel as the detection layer, and Agarose/chitosan/phthalocyanine (AG/CS/Pc) hydrogel as the treatment layer. When Staphylococcus aureus (S. aureus) infection occurs, the pH of the environment decreases, which triggers the CABP to change from its original blue color to yellow, achieving an intuitive visual transformation. Moreover, the hydrogel patch showed a significant inhibition rate of up to 99.99971 % against S. aureus under 660 nm light radiation, showing a good photodynamic therapy (PDT)/ chemotherapy (CT) synergistic effect. In addition, CABP showed excellent antibacterial and wound healing effects on S. aureus infection in a full-layer skin defect experiment. In short, the patch system is simple to prepare and easy to use, and can provide important research value for the integrated diagnosis and treatment system in biomedical applications.

Perbandingan efektivitas senyawa logam alkali sebagai zat cabut warna golongan reaktif pada batik

In making batik, the color dyeing method sometimes produces colors that are not as desired. One way to remove color pigment is by unpluging color. Apart from that, unplug color can be used as a technique to produce decorative variations on fabric. Unplug color is used to take or remove color pigments that are already on the fabric to obtain the previous color. The use of color removal agents affects the color removal results. The aim of this research is to determine the appropriate level of cleanliness for the application of scrub on fabric that is removed using calcium hypochlorite, sodium hypochlorite, sodium hydrosulfite and potassium permanganate. The research method used is field observations carried out in areas that have color removal facilities, then from the results of the data obtained an experiment will be carried out with a recipe for a removal agent of 10 grams/liter with a removal time of 10 minutes. The experimental results showed that the removal agents for calcium hypochlorite, sodium hypochlorite and sodium hydrosulfite had a color that was lighter than the original color. Meanwhile, the potassium permanganate dissolving agent produces a color that is different from the direction of the original color.

Portrait of tracy for bass guitar solo by Jaco Pastorius in the context of the application of flajeolet technique

This article presents an analysis of the application of the flageolet technique on the bass guitar in Jaco Pastorius’s composition Portrait of Tracy. Of particular interest is the musician’s endeavor to combine bass and melodic functions on the bass guitar, which makes it possible to get an additional acoustic volume. At the same time, the use by J. Pastorius of the technique of natural and artificial flageolets as the main tuning and melodic means creates a palette of bright lines and original timbre colors.

Taming Reversible Halftoning Via Predictive Luminance.

Traditional halftoning usually drops colors when dithering images with binary dots, which makes it difficult to recover the original color information. We proposed a novel halftoning technique that converts a color image into a binary halftone with full restorability to its original version. Our novel base halftoning technique consists of two convolutional neural networks (CNNs) to produce the reversible halftone patterns, and a noise incentive block (NIB) to mitigate the flatness degradation issue of CNNs. Furthermore, to tackle the conflicts between the blue-noise quality and restoration accuracy in our novel base method, we proposed a predictor-embedded approach to offload predictable information from the network, which in our case is the luminance information resembling from the halftone pattern. Such an approach allows the network to gain more flexibility to produce halftones with better blue-noise quality without compromising the restoration quality. Detailed studies on the multiple-stage training method and loss weightings have been conducted. We have compared our predictor-embedded method and our novel method regarding spectrum analysis on halftone, halftone accuracy, restoration accuracy, and the data embedding studies. Our entropy evaluation evidences our halftone contains less encoding information than our novel base method. The experiments show our predictor-embedded method gains more flexibility to improve the blue-noise quality of halftones and maintains a comparable restoration quality with a higher tolerance for disturbances.

Verification of color characteristics of document images captured in uncontrolled conditions

This paper examines a presentation attack when a color photo of a gray copy of a document is presented instead of the original color document during remote user identification. To detect such an attack, we propose an algorithm based on the comparison of chromaticity histograms of presented color images of the document and the ideal template of this type of document. The chromaticity histograms of the original document and the template are expected to be quite identical, while the histograms of the gray copy of the document and the template would be different. The algorithm was tested on images from the open dataset DLC-2021, which contains color images of synthesized identity documents and color images of their gray copies. The precision of the proposed method was 98.99 %, the recall was 84.7 %, that gave 8 times fewer errors than the baseline provided by authors of DLC-2021.

Smartphone Contact Imaging and 1-D CNN for Leaf Chlorophyll Estimation in Agriculture

Traditional leaf chlorophyll estimation using Soil Plant Analysis Development (SPAD) devices and spectrophotometers is a high-cost mechanism in agriculture. Recently, research on chlorophyll estimation using leaf camera images and machine learning has been seen. However, these techniques use self-defined image color combinations where the system performance varies, and the potential utility has not been well explored. This paper proposes a new method that combines an improved contact imaging technique, the images’ original color parameters, and a 1-D Convolutional Neural Network (CNN) specifically for tea leaves’ chlorophyll estimation. This method utilizes a smartphone and flashlight to capture tea leaf contact images at multiple locations on the front and backside of the leaves. It extracts 12 different original color features, such as the mean of RGB, the standard deviation of RGB and HSV, kurtosis, skewness, and variance from images for 1-D CNN input. We captured 15,000 contact images of tea leaves, collected from different tea gardens across Assam, India to create a dataset. SPAD chlorophyll measurements of the leaves are included as true values. Other models based on Linear Regression (LR), Artificial Neural Networks (ANN), Support Vector Regression (SVR), and K-Nearest Neighbor (KNN) were also trained, evaluated, and tested. The 1-D CNN outperformed them with a Mean Absolute Error (MAE) of 2.96, Mean Square Error (MSE) of 15.4, Root Mean Square Error (RMSE) of 3.92, and Coefficient of Regression (R2) of 0.82. These results show that the method is a digital replication of the traditional method, while also being non-destructive, affordable, less prone to performance variations, and simple to utilize for sustainable agriculture.

Effect of ultra-high pressure heat-assisted technology combined with L-cysteine on the color of ready-to-eat shrimp during storage

This study used ultra-high pressure processing (HPP) heat-assisted technology combined with L-cysteine (L-cys) to process ready-to-eat (RTE) shrimp. Subsequently, the effects of physical field and chemical modifications on the color of RTE shrimp were studied. The results showed that the RTE shrimp treated with HPP-Heat-L-cys showed better performance in terms of brightness value (65.25) and astaxanthin (AST) content (0.71 μg/g) during storage, maintaining the original color of RTE shrimp effectively. In addition, it was observed that the application of HPP-Heat-L-cys significantly delayed phenol oxidation, lipid oxidation, and Maillard reaction compared with traditional HPP or heat treatments. Specifically, the total phenolic content of RTE shrimp treated with HPP-Heat-L-cys was higher than that of other samples, but the TBARS and browning index were lower. Furthermore, HPP-Heat-L-cys could delay the production of dark products (such as 2-methylanthraquinone, p-benzoquinone, lipofuscin and melanin), ultimately safeguarding the color stability of RTE shrimp during storage.

Semantic attention guided low-light image enhancement with multi-scale perception

Low-light environments often lead to complex degradation of captured images. However, most deep learning-based image enhancement methods for low-light conditions only learn a single-channel mapping relationship between the input image in low-light conditions and the desired image in normal light without considering semantic priors. This may cause the network to deviate from the original color of the region. In addition, deep network architectures are not suitable for low-light image recovery due to low pixel values. To address these issues, we propose a novel network called SAGNet. It consists of two branches:the main branch extracts global enhancement features at the level of the original image, and the other branch introduces semantic information through region-based feature learning and learns local enhancement features for semantic regions with multi-level perception to maintain color consistency. The extracted features are merged with the global enhancement features for semantic consistency and visualization. We also propose an unsupervised loss function to improve the network’s adaptability to general scenes and reduce the effect of sparse datasets. Extensive experiments and ablation studies show that SAGNet maintains color accuracy better in all cases and keeps natural luminance consistency across the semantic range.

A modified hue and range preserving color assignment function with a component-wise saturation adjustment for color image enhancement

This paper presents a new approach to enhancing color images by modifying an affine color assignment function. This function maps colors to pixels of the enhanced gray-scale image in a way that improves the visual quality of the image, particularly in darker regions. The main goal of our method is to finely adjust saturation, correct saturation loss in specific image regions, and preserve the original image’s range and hue. Our proposed method follows a two-step process. First, it enhances the intensity image using a combination of global and local histogram equalization methods. This results in an overall improved appearance by redistributing pixel intensities and enhancing contrast. Then, modified color mapping functions are applied to assign colors to each pixel of the enhanced gray-scale image. The aim is to adjust saturation by amplifying the maximally saturated color image. Additionally, we introduce two new color-weighted maps to evaluate pixel importance from the maximally saturated image. This contributes to saturation control in the final enhanced image. Compared to alternative color mapping algorithms, our model preserves the original color of pixels in challenging areas and fine-tunes saturation based on parameter settings.

A photochromic double-polyanion-type arsenotungstate

A double-polyanion-type arsenotungstate, namely [H2N(CH3)2]14H8.5[Si0.5As0.5W18O62][BaNa2{As2W19O67(H2O)}]·29H2O was prepared by self-assembly strategy of some simple raw materials, in which a Dawson-type [Si0.5As0.5W18O62]12.5− polyanion and a [BaNa2{As2W19O67(H2O)}]10− polyanion co-exist in the lattice. Two half-occupied Ba2+ ions were inserted into the pocket-shaped vacancies of {As2W19} building blocks, while two Na2+ ions served as connectors bridging adjacent units. Furthermore, dimethylamine cations play a vital role in building a hydrogen bond network with the polyoxometalate skeleton to maintain the framework of the solid-state compound 1. In addition, being characterized under the 300 W Xe-lamp, the color of compound 1 changed from light green to bluish grey after 210 s with recovery to its original color after about 14 h treating with darkness, displaying a reversible photochromism.

Shadow removal method for high-resolution aerial remote sensing images based on region group matching

Shadow removal is a critical step in preprocessing high-resolution aerial remote sensing images. The presence of shadows reduces the information in high-resolution aerial remote sensing images, lowers the image quality, and seriously interferes with the work of feature classification, object detection, and information extraction. Therefore, this paper proposes a high-resolution aerial remote sensing image shadow removal method based on region group matching. The method starts from both spatial information and color information, and is able to take into account the whole and the local, and recover the detailed features of different features inside the shadows. Firstly, this paper proposes an irregular region color transfer method based on three-dimensional color space, which can effectively restore the original color and texture information of the features in the shadow region. Secondly, considering the random and variable direction of feature distribution in remote sensing images, the direction of texture feature extraction cannot be set in advance. Therefore, in this paper, the texture details of the features are extracted based on the rotationally invariant light-independent texture feature extraction method to exclude the abnormal interference. Then, the shadow and light regions of the image are segmented internally and grouped according to the type of features to avoid subsequent matching anomalies due to the small size of the image blocks. Next, construct an average texture feature vector for each group of image blocks for grouping matching. The matched light groups are then used to guide the shadow groups for local feature information enhancement, which ensures that on top of the overall shadow removal, the detail recovery of different local features is enhanced. Finally, for the boundary effect after shadow removal, a boundary optimization method with dynamically assigned weights is proposed, which can ensure the natural coherence of the resultant image in the boundary part. The experimental results show that the proposed method balances both overall and local shadow removal effects and can effectively achieve high-resolution aerial remote sensing image shadow removal. Compared with existing methods, the proposed method achieves the best quality of shadow removal results and restores more realistic ground features in shadow region.

Illumination correction for dyed products with spotted hyena optimizer and regularized extreme learning machine

Dyed products exhibit varying colors when illuminated by different light sources. Human eyes possess color constancy, enabling them to automatically adjust and overlook color discrepancies, effectively self-correcting visually. However, these variations are perceived as distinct colors by computers. To eliminate the effects of lighting on the dyed products, illumination correction is needed to make the dyed products show their original color. To achieve this goal, this article presents a novel algorithm, WOA-SHO-RELW (Whale Optimization Algorithm-Spotted Hyena Optimizer-Regularized Extreme Learning Machine), designed to emulate color constancy and applies it to the illumination correction of dyed products. We employ the WOA to optimize the initial population of SHO, carefully selecting a group of suitable initial parameters. Subsequently, SHO is utilized to optimize the hidden biases and input weights of RELM, with the overarching aim of enhancing the model’s effectiveness and performance, thereby ensuring more precise illumination correction for images of dyed products. The comparison results with other algorithms show that our WOA-SHO-RELM has better comprehensive performances.

Tuning Spatially Resolved Shape Memory Effects of Stimuli‐Responsive Macroporous Photonic Crystals

Stimuli‐responsive photonic crystals with patterned microstructures are of great interest in developing reconfigurable nano‐optical devices. Leveraging unconventional all‐room‐temperature shape memory efforts and spatially resolved photopolymerization, herein, a facile method for micropatterning stimuli‐responsive photonic crystals is reported. Macroporous shape memory polymer (SMP) photonic crystals fabricated by colloidal templating can be deformed by cold programming, triggering the disappearance of their original structural colors. Exposure of the deformed samples to UV light through a photomask selectively disables the shape memory capabilities in the UV‐exposed regions. Hidden micropatterns defined by the photomask can be revealed by exposing the colorless SMP films to ethanol vapor, which triggers the shape memory recovery of the “memorized” ordered microstructures and the corresponding structural colors. Extensive nanoindentation experiments indicate that the exposure to UV light increases the crosslinking density and enhances the elastic modulus and toughness of the exposed regions by a factor of ≈2.0 and ≈5.2, respectively. Due to the formation of these extra crosslinks in the deformed configuration, they prevent normal shape memory behavior where the strained polymer chains rearrange from the temporary to permanent configuration when triggered by an external stimulus. This simple micropatterning technology can enable multistimuli‐responsive reconfigurable nanophotonic devices and chromogenic anticounterfeiting labels.

The Little Book of Trees

From the publisher: Packed with surprising facts, this delightful and gorgeously designed book will beguile any nature lover. Expertly written and beautifully illustrated throughout with color photographs and original color artwork, The Little Book of Trees is an accessible and enjoyable mini-reference about the world’s trees, with examples drawn from across the globe. It fits an astonishing amount of information in a small package, covering a wide range of topics—from tree anatomy, diversity, and architecture to habitat and conservation. It also includes curious facts and a section on trees in myths, folklore, and modern culture from around the world. The result is an irresistible guide to the amazing lives of trees.

Quasi-projective synchronization of non-identical time-varying delayed quaternion-valued neural networks with interaction terms: Direct method

This article investigates the quasi-projective synchronization (QPS) of non-identical quaternion-valued neural networks (QVNNs) with time-varying delays and interaction terms. Due to parameter mismatches between the drive and response systems, complete projective synchronization is not possible. As a result, a novel idea, known as QPS, is explored up to a small error bound. The direct method is used to derive several general criteria to achieve QPS. The Lyapunov stability theory is employed to estimate the error bound. The numerical simulation results are presented graphically for various special cases to demonstrate the synchronization of time-varying delayed QVNNs with mismatched parameters and interaction terms, which confirm the efficiency of the presented research results. The second example showcases the application of QVNNs coupled with associative memory to illustrate its efficacy in accurately restoring the original color image patterns.

Low‐Emissivity Patterned Camouflage for Visible and Infrared Stealth

The development of multispectral detection emphasizes the significance of multispectra‐compatible camouflage technology, necessitating compatible camouflage for visible and infrared bands. Conventional painted camouflage is hindered by high infrared emissivity, and crafting patterns with existing low‐emissivity materials is hindered by the lack of adequate colors. Herein, this study introduces a method to reduce the emissivity while maintaining its original color. By covering a metafilm that reflects most infrared radiation on conventional patterned camouflage, low‐emissivity coatings are achieved. The thickness of the metafilm is optimized, effectively reducing color differences between uncoated and coated camouflage. Monochromatic substrates with the metafilm retain original colors with small color differences (e.g., 0.61) and demonstrate low infrared emissivity (0.03). Patterned camouflage yields an area‐weighted color difference of 9.09 with an infrared emissivity of 0.05. Experimental application on grassland backgrounds demonstrates visual integration with the background. Infrared thermography shows that coated camouflages, compared to uncoated ones, exhibits significantly reduced radiant temperature (29.5 °C vs. 43.0 °C) when heated to 50 °C against a 29.5 °C background, enhancing its blending capability. This metafilm effectively mitigates infrared emissivity while maintaining original colors and patterns, facilitating efficient camouflage across visible and infrared spectrums.