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Due to the instability of the hyperspectral imaging system and the atmospheric interference, hyperspectral images (HSIs) often suffer from losing the image information of areas with different shapes, which significantly degrades the data quality and further limits the effectiveness of methods for subsequent tasks. Although mainstream deep learning-based methods have achieved promising inpainting performance, the complicated ground object distributions increase the difficulty of HSIs inpainting in practice. In addition, spectral redundancy and complex texture details are two main challenges for deep neural network-based inpainting methods. To address the above issues, we propose a Global-Local Constraints-based Spectral Adaptive Network (GLCSA-Net) for HSI inpainting. To reduce the redundancy of spectral information, a multi-frequency channel attention module is designed to strengthen the essential channels and suppress the less significant ones, which calculates adaptive weight coefficients by converting feature maps to the frequency domain. Furthermore, we propose to constrain the generation of missing areas from both global and local perspectives, by fully leveraging the HSI texture information, so that the overall structure information and regional texture consistency of the original HSI can be maintained. The proposed method has been extensively evaluated on the Indian Pines and FCH datasets. The promising results indicate that GLCSA-Net outperforms the state-of-the-art methods in quantitative and qualitative assessments. [ABSTRACT FROM AUTHOR]

This paper aims to explore the narrative expression skill of design students through manipulating image structure. Moreover, narrative expression is the skill of interpreting design with narrative. The study is a classroom experiment conducted naturally, and the experimental data is obtained and analysed by quantitative analysis. We found differences in students' narrative tendencies and richness in overall narrative expression. The teaching and training of design narrative can effectively help students familiarise themselves with the design process and personal skill integration and encourage students to pay attention to the design of elements and content. This will improve students' design competencies under skills different from technology. The paper concludes that students must improve and integrate design competencies through practical methods under other narrative tendencies. Furthermore, the lecturer can explore and adjust design teaching through design narrative training to strengthen or balance students' design performance competency. [ABSTRACT FROM AUTHOR]

Copyright of Central Asian Journal of Art Studies is the property of Central Asian Journal of Art Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Seam carving algorithm is widely used in content-based image scaling. By calculating the energy map of the image, it repeatedly removes the pixel line with the lowest energy sum, which can effectively retain the proportion of significant areas within the image after the image is scaled down. The traditional seam carving does not take into account the variation in full-image energy caused by each carving, which is based on the energy map calculated at the first time. The results of these methods are prone to distortion. So we put forward a dynamic energy regulation method to simulate the energy change in each carving to improve the effect of seam carving. Our method adjusts the energy value of each pixel after each carving according to how much each pixel is affected by carving, so as to simulate the extra energy introduced by each carving. In the paper, we discuss the way to regulate energy. We designed a randomized double-blind experiment to compare our method with several current typical methods. The experimental results demonstrated the advantages of our method over other methods. [ABSTRACT FROM AUTHOR]

Existing deep learning-based shadow removal methods still produce images with shadow remnants. These shadow remnants typically exist in homogeneous regions with low-intensity values, making them untraceable in the existing image-to-image mapping paradigm. We observe that shadows mainly degrade images at the image-structure level (in which humans perceive object shapes and continuous colors). Hence, in this paper, we propose to remove shadows at the image structure level. Based on this idea, we propose a novel structure-informed shadow removal network (StructNet) to leverage the image-structure information to address the shadow remnant problem. Specifically, StructNet first reconstructs the structure information of the input image without shadows and then uses the restored shadow-free structure prior to guiding the image-level shadow removal. StructNet contains two main novel modules: 1) a mask-guided shadow-free extraction (MSFE) module to extract image structural features in a non-shadow-to-shadow directional manner; and 2) a multi-scale feature & residual aggregation (MFRA) module to leverage the shadow-free structure information to regularize feature consistency. In addition, we also propose to extend StructNet to exploit multi-level structure information (MStructNet), to further boost the shadow removal performance with minimum computational overheads. Extensive experiments on three shadow removal benchmarks demonstrate that our method outperforms existing shadow removal methods, and our StructNet can be integrated with existing methods to improve them further. [ABSTRACT FROM AUTHOR]

The notion of multifaceted image, composed of cognitive, affective, and sensory dimensions, has attracted growing scholarly interest in recent years. However, general understanding of the roles of the senses (i.e., sight, hearing, taste, smell, and touch) in image processing remains scarce. Little attention has also been paid to the effects of visual stimuli related to design features on the construction of multifaceted image. This study investigated viewers' perceived multifaceted destination image upon exposure to different photo formats (i.e., animated vs. static). A mixed method approach was employed to collect data using a between-subjects experimental design. Findings revealed that moving visual presentation exert stronger impacts on three image dimensions in several aspects and associations were also observed between photo contents and sensory arousal. Results enrich the body of knowledge on destination image in terms of image structure and the features of visual stimuli. Practical implications are discussed as well. [ABSTRACT FROM AUTHOR]

Abstract The relationship between culture and the appeals in TV advertisements has been extensively studied. We attempted to reveal the image structure produced by TV commercials in Japan, which may show the cultural features of the country, and to evaluate its temporal change. For this purpose, we constructed and analysed a co-occurrence network of keywords related to TV commercials by using immense data that include the records of all TV commercials aired in the Kanto area in Japan including Tokyo for a period of 15 years. We found a strong heterogeneity of the co-occurrence relationship, where a few keywords, e.g., ‘woman’, ‘man’, ‘animation’, and ‘logo’, co-occur with a huge number of other keywords every year. A community on a co-occurrence network can be regarded as a set of keywords that are mutually associated with each other through TV commercials. We examined the characteristics of the communities by associating them with categories of advertised products and found a temporal change in which the relationship between the communities possessing the image of entertainment and children and the category of PC and A/V gradually increases in strength. However, there was a consistent tendency in the examined period for the product categories related to communities that include ‘man’ to be less associated with those that include ‘woman’ and vice versa, which implicates a gender role inequality underlying the various appeals in TV commercials.

The gradient vector flow (GVF) model has been widely used in the field of computer image segmentation. In order to achieve better results in image processing, there are many research papers based on the GVF model. However, few models include image structure. In this paper, the smoothness constraint formula of the GVF model is re-expressed in matrix form, and the image knot represented by the Hessian matrix is included in the GVF model. Through the processing of this process, the relevant diffusion partial differential equation has anisotropy. The GVF model based on the Hessian matrix (HBGVF) has many advantages over other relevant GVF methods, such as accurate convergence to various concave surfaces, excellent weak edge retention ability, and so on. The following will prove the advantages of our proposed model through theoretical analysis and various comparative experiments. [ABSTRACT FROM AUTHOR]

Formulation of the problem. The educational sector reform, including higher education in Ukraine and its entry into the European space has changed the requirements not only for teachers. The universities image is changing, both on the part of the state and higher education institutions, and on the part of the public and students. Nowadays the educational institution success should be complemented by its individuality manifestation, an indicator of which is a certain level of image formation of the higher educational institution. The staff uniqueness of the educational institution is its component. Thus, there is no doubt about the relevance of this problem and its practical solution significance. It should be noted that the issue of the higher educational institution image creation needs to be studied. The scientific developments on the research topic are analyzed and the issue of formation of the higher educational institution image as a pedagogical problem, that requires detailed research, is clarified in this article. Materials and methods. In the scientific process, dissertation research materials, pedagogical and scientific literature were used. To achieve the goal of the study theoretical and empirical methods: analysis and systematization; observation; written and oral interview; analysis, systematization, generalization were used. Results. The following trends in the formation of the higher educational institution image should be proposed: - the management and teaching staff of the higher educational institution should consider the university image as a condition for ensuring its positioning in the market and increasing its competitiveness; - the presence of the higher educational institution image should be associated with an increase in the prestige, and, consequently, the authority and influence of the higher educational institution in the state; - the higher educational institution image influences the choice of an educational institution by students as a base for vocational training. Conclusions. Thus, an effective strategy for the formation of the higher educational institution image is a tool for influencing the perception of a higher educational institution by various subjects and stakeholders’ groups, which increases its competitiveness potential.

The purpose of single-image super resolution (SISR) is to reconstruct an accurate high-resolution image from a degraded low-resolution image. Owing to the lack of information in low-resolution images, SISR is a challenging problem. In particular, it is difficult to represent details, including high-frequency components, such as texture and structural information. We propose the edge profile super-resolution (EPSR) method to preserve structural information and restore texture. EPSR is achieved by stacking modified fractal residual network (mFRN) structures hierarchically and repeatedly. Each mFRN is composed of many residual edge profile blocks (REPBs) that extract features and preserve the edge, structure, and texture information of the image. For implementing REPB, we design three main modules: Residual Efficient Channel Attention Block(RECAB) module, Edge Profile(EP) module, and Context Network(CN) module. By repeating the procedure in the mFRN structure, the EPSR method could be used to extract high-fidelity features, thus preventing texture loss and preserving the structure with appropriate sharpness. Experimental results show that EPSR achieves competitive performance against state-of-the-art methods in terms of the peak signal-to-noise ratio(PSNR) and structural similarity index measure(SSIM) evaluation metrics, as well as visual results.

The results of an empirical study of the image of the father in older adolescents living in the territory of the Republic of Tyva have been outlined. Our research is devoted to the image of the father in the Republic of Tyva. The contradictions of the mental mechanisms of the image of the father are currently changing from the traditional image of the father as a man and as a parent. The results of an empirical study of the image of the father in older adolescents 15–16 years of age from full and incomplete families of different types have been presented in the article. During the study V. L. Sitnokov’s Human Image Structure (Hierarchical) method was used. This method allows you to identify the structure of the image of the father in adolescents from full and incomplete families of different types in the Republic of Tyva.

The question about the difference (or the absence of it) between Dostoevsky’s early texts and the works composed after the penal labors have been raised repeatedly. The article proposes a possible explanation of it. The hypothesis here presented and exemplified through the analysis of the novel Netochka Nezvanova should be considered mainly as an invitation to discussion, more than the proposal of a final answer to the problem. The article suggests that we should look for the difference between earlier and later works within the level on which Dostoevsky assembles the material as a coherent storyline. While later works show coherency on an external plot level and reach the deep level of the text by connecting different scenes to episodes of the Sacred History; early works are connotated by extremely incoherent plots, which provoked (and provokes nowadays) many complaints about Dostoevsky’ authorial skills: in fact, the coherent history takes place within a deeper, being-related perspective, while the incoherent episodes of the outer tale are no more than a manifestation on an existential level of the inner “anagogic” story.

Votive rugs are in fact a kind of small pictorial rugs with an approximate size of 25 x 20 cm that are placed in various designs and colors in the middle of the platform or sometimes hung on the wall of Ghadamgah (Foothold of saints and holy people in past). These rugs are as a decorative and religious element in most of the south Qadamgah of Kerman, especially in Jiroft that share similarities from the point of view of the texture, pattern, and symbolic signs.s, and geometric symbols in the visual structure of the Votive rugs, and main question in this research is, how is the visual structure and composition of the painting of the Votive rugs and what is symbolic meanings based on popular culture? The visual structure and composition of the rug consists of two parts, the margin and the text. The textures of the rugs are wiew in structure, form, image, text or composition. The method of collecting information in this field research is using archaeological resources, historical documents, collecting visual samples and oral interviews with villagers and tribesmen in Jiroft region and the analytical comparative research method is a semantic approach. Since the issue of Votive is a personal and spiritual matter,. the goals of the weavers identified, but based on the images and the name of the prophets, it seems to be requests for prayer and happiness on the text of the weaving rugs that these works have a certain religious and ceremonial function,

Most of all Dostoevsky’s texts, “The Beggar Boy at Christ's Christmas Tree” poses questions about the structure of image in the author’s works, and about the intentional focus of the literary text, aiming to offer the reader another view of the reality surrounding him, to “wash” his/her eyes, covered by the dirt flowing from “the proximate and the visible in its flowing immediacy” and closed by the crust of humdrum. Solving the question of the structure of the image allows us to answer the question of how deepness is reached in Dostoevsky’s texts. The two-fold image in Dostoevsky’s works is described, as well as its analogues in the Christian culture, the qualities and characteristics of such an image, the way it is shaped through the reproduction of iconic images or through allusions to the Gospels, and its essential role in creating a space for the reader’s personal action. The article also concerns the differences occurring between this kind of image and another one – the Symbolists’ image – whose aim was to awake memories, to recognize and to comprehend the permanent patterns of human actions and relations, but not to change these patterns. The tale displays a double layer concerning not only human, but also space images, the presence of the already transfigured space in the depth of mundanity, whose appearance is prevented by human indolence, indifference, and the fact of being focused on the self.

I present a personal account of the origin, development and future of a concept that appeared in this journal in 1984. The title was The Structure of Images. It became known as "scale space." [ABSTRACT FROM AUTHOR]

This paper addresses the analysis of textured images using the symmetric positive semi-definite matrix. In particular, a field of symmetric positive semi-definite matrices is used to estimate the structural information represented by the local orientation and the degree of anisotropy in structured and sinusoid-like textured images. In order to ensure faithful local structure estimation, an adaptive algorithm for the regularization of the extent of gradient fields smoothing is proposed. Results obtained on different texture samples show the strength of the proposed method in accurately representing the local variation of orientations in the underlying textured images, which paves the way towards an accurate analysis of the texture structures.

Image regularised features play a critical role in image processing domain, by integrating regularised feature and structural similarity, a new full‐reference image assessment method (IRF_SSIM) is proposed in this study. As well known, the gradient operator always be used to capture the edge information of the image, while the total variational regularised features can be adopted to calculate the detailed change information of image contrast and texture, as well as noise removal and edge retention. Therefore, the IRF_SSIM method extends the gradient features into the image regularised features to measure the structural changes in the image. In addition, image quality is also affected by variations of luminance and contrast. For a more comprehensive image quality assessment, the IRF_SSIM method considers the changes in structure, luminance and contrast simultaneously. In other words, the total image quality is estimated by structural similarity calculated by integrating the effects of image structure, luminance and contrast changes. Comparing with the representative methods, the experimental results illustrate that the IRF_SSIM method is highly consistent with the subjective assessment results. [ABSTRACT FROM AUTHOR]

Just-noticeable difference (JND) is defined as the smallest intensity change in an image that can be noticed by the human vision system (HVS). Any perceptible distortion level must be greater than the JND. Based on this observation, a local binary pattern (LBP) is developed for image quality assessment. First, the JND map of the image is computed. The spatial and relative intensity relationships among pixels in a local neighborhood are employed to generate the proposed LBP based on the JND map. Then, image contrast is used as a weighting factor for the LBP histogram generation to characterize the structural and contrast information of the image. Finally, the contrast and structure changes due to image distortion are measured by calculating the similarity between contrast-weighted histograms of the reference and distorted images. Support vector regression is employed to pool the similarity to predict the quality. Experimental results on benchmark databases demonstrate that the proposed LBP can effectively and accurately measure image quality, which is consistent with the HVS. The proposed method achieves high consistency with subjective perception using 18 reference values and performs better than other state-of-the-art reduced reference image quality assessment methods. [ABSTRACT FROM AUTHOR]

Image restoration has attracted substantial attention recently and many image restoration algorithms have been proposed for restoring latent clear images from degraded images. However, determining how to objectively evaluate the performances of these algorithms remains an open problem, which may hinder the further development of advanced image restoration techniques. Most image restoration-quality metrics are designed for specific restoration applications; hence, their generalization ability is limited. For benchmarking image restoration algorithms, the ranking of restored images that are generated via various algorithms, is the most heavily considered factor. Inspired by this, this paper presents a pairwise-comparison-based rank learning framework for benchmarking the performances of image restoration algorithms, which focuses on the relative quality ranking of restored images. Under the proposed framework, we further propose a general image restoration quality metric by integrating quality-aware features in both the spatial and frequency domains. The proposed metric exhibits good generalization performance, and it is applicable to various restoration applications. The results of extensive experiments that were conducted on eight public databases of five restoration scenarios demonstrate the superior performance of the proposed method over the existing quality metrics. Moreover, the proposed framework is used to improve the existing quality metrics for benchmarking image restoration algorithms and highly encouraging results are obtained. [ABSTRACT FROM AUTHOR]

Perceiving the spatial layout of objects is crucial in visual scene perception. Optic flow provides information about spatial layout. This information is not affected by image blur because motion detection uses low spatial frequencies in image structure. Therefore, perceiving scenes with blurry vision should be effective when optic flow is available. Furthermore, when blurry images and optic flow interact, optic flow specifies spatial relations and calibrates blurry images. Calibrated image structure then preserves spatial relations specified by optic flow after motion stops. Thus, perceiving blurry scenes should be stable when optic flow and blurry images are available. We investigated the types of optic flow that facilitate recognition of blurry scenes and evaluated the stability of performance. Participants identified scenes in blurry videos when viewing single frames and the entire videos that contained translational flow (Experiment 1), rotational flow (Experiment 2) or both (Experiment 3). When first viewing the blurry images, participants identified a few scenes. When viewing blurry video clips, their performance improved with translational flow, whether it was available alone or in combination with rotational flow. Participants were still able to perceive scenes from static blurry images one week later. Therefore, translational flow interacts with blurry image structures to yield effective and stable scene perception. These results imply that observers with blurry vision may be able to identify their surrounds when they locomote. [ABSTRACT FROM AUTHOR]

The aim of this study is to reveal the opinions of the architect in the design of Konya Science Center, to analyze the relationship established by the structure with the city, its scale with surrounding texture and human, the access to structure, its form, material, technology and its spatial presentation to determine whether it is an image structure or not. For this purpose, science centers’ design purpose and their importance for the city are explained at first, examples across the world are given. Observations and interviews are made, photographs of the structure are taken and any kind of written and drawn resources are utilized in order to determine whether the selected structure is in accordance with the definition “image structure”. As a result, it is determined with this study that Konya Science Center is “an image structure” for the city in parallel with the developing trends in design and construction technology fields in general terms after its analysis in architectural terms.

This paper presents the results of a study of the relationship between the bank image, its structure as a reflection in the minds of individuals and behavioural tendencies in relation to banks. Attitudinal scales were used to identify the contents of the particular banks’ image. The structure of the image was identified by means of factor analysis. The study found that the respondents’ behavioural tendencies, i.e. their willingness to be a client of or to recommend a particular bank, are related to different content components of particular banks and mainly to respondents’ needs. Based on the results, the study identifies the danger that the results of the bank image analysis can be misinterpreted if the respondents’ relationship to the bank is underestimated.

Copyright of Al-Bahith Al-Aalami is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We consider image intrinsic structure in two aspects: foreground saliency computation and background saliency calculation. On the one hand, a segmented image is represented as a weighted undirected graph, and we calculate the foreground saliency by choosing some superpixels as ranking queries, where we apply a robust background measure to select those for accuracy. On the other hand, we compute the posterior probabilities to measure the background saliency and in terms of the probability, we construct a probability tree via multimerging on superpixels, and then apply the optimization strategy to the background saliency. We evaluate our proposed algorithm on two benchmark datasets and our algorithm yields the competitive results when compared with nine state-of-the-art algorithms in terms of five evaluation metrics. [ABSTRACT FROM AUTHOR]

After the Commune and the terrible defeat in the war of 1870, J.-K. Huysmans, Jules Barbey d’Aurevilly, and others created a kind of art based on hedonism, beauty, a refined style, and analogical (or metaphoric) structures. Flavoured with decay and death, their decadentism wasfin-de-siècle, perhapsla fin du monde. In the midst of some posturing, J.-K. Huysmans and Jules Barbey d’Aurevilly called the importance of plot into question, while exploiting the growing controversy to introduce decadent works organized by embedded themes and images. Later writers from the same tradition, like Gide and Proust, adopted the decadents’ analogical structures and reintroduced traditional narrations, frequently opposing one to the other. [ABSTRACT FROM PUBLISHER]