Image Restoration Strategies Research Articles

Defiance as an image restoration strategy: refining the reputation risk management framework

Purpose This study aims to develop an understanding of strategies used by two major banks in Australia to manage reputation risk after court proceedings were initiated by the government for serious breaches of the Anti-Money Laundering and Counter-Terrorism Financing Act 2006. Design/methodology/approach The study is grounded in the corporate social responsibility (CSR) and image restoration literature. Thematic analysis of court proceedings, banks’ annual report suites (which include sustainability reports) and media reports was undertaken using the conceptual framework of reputation risk management (RRM). Findings A major new strategy of image restoration – defiance – emerged. It is contended that the existing RRM framework needs to be refined. Similarly, in the reducing effectiveness strategy, two new sub-strategies need to be included: refusal to acknowledge an incident as reputational damage and acceptance of the statutory penalty without legally challenging it. The banks also used traditional strategies of the RRM framework, such as reducing effectiveness by minimisation, bolstering, corrective action and mortification. Originality/value Trustworthiness and confidence are at the core of modern banking. Banks use CSR disclosures as the principal means for image restoration. The present paper explores the link between extant CSR literature and RRM.

Image restoration strategies in pandemic crisis communication: a comparative analysis of Chinese and American COVID-19 political speeches

This study explores the effectiveness of image restoration strategies in pandemic crisis communication at the highest levels of administration. By integrating corpus-assisted discourse analysis with Image Repair Theory, it aims to uncover the prevailing strategies adopted by Chinese and American leaders to restore or enhance a positive national image in the post-COVID era. Lancsbox 6.0 was utilized to extract excerpts and analyze linguistic devices from a self-built corpus of 144 political speeches delivered by top leaders in China and the United States. The results reveal that Chinese leaders, through the use of shared image restoration strategies such as bolstering and transcendence, shape a positive national image of a responsible country. In contrast, American leaders construct a confident and ambitious national image, projecting a leading geopolitical role in the world. These strategies have distinct features that contribute to the image restoration process. Apart from contributing significantly to the comparative research on Chinese and American pandemic-related political speeches, the research findings carry implications for the practice and promotion of national ideologies. The study also highlights the diverse ways in which credible and accurate crisis messages are employed, providing valuable insights for handling pandemics or other crises in the foreseeable or distant future.

Gaussian second derivative blur kernels for image deblurring

Image blur is a common image degradation phenomenon that occurs in case of camera movement and lens defocusing. In order to deblur the image, point spread function (PSF) model is often used to match the real blur kernel, but currently the matching effect is poor. In this paper, an image restoration technique based on the Gaussian Second Derivative (GSD) fitted PSF is proposed to address this problem. Firstly, a GSD model is proposed. The actual image Line spread function (LSF) extracted by knife-edge method is modeled as a linear combination of a series of Gaussian second derivatives. Then, an improved annihilation filtering algorithm is proposed. The algorithm is used to estimate the parameters of the GSD model, so as to remove the errors in the actual complex scenarios. Finally, the image PSF is obtained by using the LSF curve fitted and corrected by the GSD model, and combined with the existing Richardson-Lucy (R-L) algorithm, the clear image is finally restored. Experimental results show that compared with the existing image restoration strategies based on other PSF models, this method can effectively improve the image restoration accuracy.

Deep demosaicking convolution neural network and quantum wavelet transform-based image denoising

ABSTRACT Demosaicking is a popular scientific area that is being explored by a vast number of scientists. Current digital imaging technologies capture colour images with a single monochrome sensor. In addition, the colour images were captured using a sensor coupled with a Colour Filter Array (CFA). Furthermore, the demosaicking procedure is required to obtain a full-colour image. Image denoising and image demosaicking are the two important image restoration techniques, which have increased popularity in recent years. Finding a suitable strategy for multiple image restoration is critical for researchers. Hence, a deep learning (DL) based image denoising and image demosaicking is developed in this research. Moreover, the Autoregressive Circle Wave Optimization (ACWO) based Demosaicking Convolutional Neural Network (DMCNN) is designed for image demosaicking. The Quantum Wavelet Transform (QWT) is used in the image denoising process. Similarly, Quantum Wavelet Transform (QWT) is used to analyse the abrupt changes in the input image with noise. The transformed image is then subjected to a thresholding technique, which determines an appropriate threshold range. Once the threshold range has been determined, soft thresholding is applied to the resulting wavelet coefficients. After that, the extraction and reconstruction of the original image is carried out using the Inverse Quantum Wavelet Transform (IQWT). Finally, the fused image is created by combining the results of both processes using a weighted average. The denoised and demosaicked images are combined using the weighted average technique. Furthermore, the proposed QWT+DMCNN-ACWO model provided the ideal values of Peak signal-to-noise ratio (PSNR), Second derivative like measure of enhancement (SDME), Structural Similarity Index (SSIM), Figure of Merit (FOM) of 0.890, and computational time of 49.549 dB, 59.53 dB, 0.963, 0.890, and 0.571, respectively.

The Effect of Consumer Perception and Image Restoration Strategy on Organization-Public Relationship (A Case Study of Mcdonald’s Indonesia Facing Boycott of Pro-Israel Products)

Objective: The objective of this study is to investigate how organizations can navigate public perception and repair their image during challenging situations. with the aim to examine the effect of consumer perception and the role of McDonald's Indonesia's image restoration strategies through media coverage on organization-public relationships. Theoretical Framework: In this topic, the main concepts and theories that underpin the research are presented. Study case stand out, providing a solid basis for understanding the context of the investigation. Method: This study adopts a quantitative approach, involving the collection, analysis, and interpretation of data to measure and generalize findings from the research sample across various perspectives to attest hypotheses. The research aims to explore the impact of consumer perceptions of McDonald's Indonesia on the organization-public relationship through image restoration strategies following the boycott of pro-Israel products. Results and Discussion: The results obtained revealed indicate a significant positive effect of consumer perception on the organization-public relationship conducted by McDonald’s Indonesia. Additionally, three image restoration strategies—evade responsibility, reduce the offensiveness, and corrective action—participate in effecting organization-public relationships. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of Crisis Communication and Public Relations. These implications could encompass how McDonald's Indonesia, facing a boycott due to a political situation, attempts to repair its public image. It analyzes the role of consumer perception and different communication strategies in this context. Originality/Value: This study contributes to the literature by Examines consumer perception in a specific cultural context , Analyzes the effectiveness of image restoration strategies, and Focuses on a specific consumer group. The relevance and value of this research are evidenced by contributes to the field of crisis communication and public relations by examining consumer perception and image restoration strategies in a specific cultural context with a particular consumer group.

Police Image Restoration: A Case Study of the Stampede (Crowd Crisis) at Kanjuruhan Malang

On October 1 2022, 131 people died in a "riot" at the Kanjuruhan Stadium, Malang, East Java. The riot occurred after Persebaya silenced Arema, the host football group. Arema supporters, who did not accept the defeat, then rushed into the stadium, so that the police (Polri) who were on guard at the location, dispersed the crowd by spraying tear gas, leaving the exit doors tightly closed, thus triggering massive panic. What happened in Kanjuruhan was an example of a stampede or crowd crisis which created chaotic conditions to the point that many were found dead. The aftermath of the tragedy was the erosion of public trust in the National Police institution. This research outlines the image restoration strategy of the National Police in overcoming the Kanjuruhan stampede, using Bennoit's Image Restoration theory. This qualitative research uses descriptive analysis to explain this phenomenon. The research results show that strategies to improve the image of the National Police, including denial, evading responsibility, reducing effectiveness, corrective action, mortification, have in fact proven to be ineffective. Because, this strategy failed to boost the institution's positive image. Thus, public trust in this institution has collapsed to this day.

Strategi pemulihan citra publik pada kementerian pemuda dan olahraga RI

The KONI Grant Fund Bribery corruption case at the Ministry of Youth and Sports violated the integrity pact, which decreased public trust. This research aims to analyze the types of image restoration strategies implemented by the Ministry of Youth and Sports and which strategies most influence public trust or can restore the image of the Ministry of Youth and Sports. The research uses a mixed sequential exploratory approach (starting from the qualitative method stage and continuing to the quantitative method). The research results show that the Ministry of Youth and Sports implements six image restoration strategies to increase the level of public trust, namely: reducing offensiveness strategy, mortification strategy, denial strategy, evading of responsibility strategy, and corrective action strategy. A new strategy, the professional imaging strategy, was discovered by the Ministry of Youth and Sports. The results of the causality analysis show that the evading of responsibility and mortification strategies have the most significant influence in increasing public trust. On the other hand, the Ministry of Youth and Sports needs to avoid professional imaging strategies because, statistically, it negatively and significantly decreases public trust. Recommendations from the Ministry of Youth and Sports need to convince the public that the KPK OTT case of KONI Grant bribery does not represent the agency and that the Ministry of Youth and Sports is committed to controlling employee performance by prioritizing integrity.

A Multi-Task Learning and Knowledge Selection Strategy for Environment-Induced Color-Distorted Image Restoration

Existing methods for restoring color-distorted images in specific environments typically focus on a singular type of distortion, making it challenging to generalize their application across various types of color-distorted images. If it were possible to leverage the intrinsic connections between different types of color-distorted images and coordinate their interactions during model training, it would simultaneously enhance generalization, address potential overfitting and underfitting issues during data fitting, and consequently lead to a positive performance boost. In this paper, our approach primarily addresses three distinct types of color-distorted images, namely dust-laden images, hazy images, and underwater images. By thoroughly exploiting the unique characteristics and interrelationships of these types, we achieve the objective of multitask processing. Within this endeavor, identifying appropriate correlations is pivotal. To this end, we propose a knowledge selection and allocation strategy that optimally distributes the features and correlations acquired by the network from the images to different tasks, enabling a more refined task differentiation. Moreover, given the challenge of difficult dataset pairing, we employ unsupervised learning techniques and introduce novel Transformer blocks, feedforward networks, and hybrid modules to enhance context relevance. Through extensive experimentation, we demonstrate that our proposed method significantly enhances the performance of color-distorted image restoration.

Strategi komunikasi image restoration mantan narapidana kasus narkoba di Aceh Tengah

In general, former prisoners want to participate socially so that their status is the same as that of other members of society. However, in reality, they often face social discrimination and negative stigma from their environment. This research question is: What is the message from former convicts in drug cases in the strategy to restore self-image in Central Aceh Regency? This research uses qualitative methods to obtain in-depth and natural data. Image Restoration Theory by William L. Benoit's is used as an analytical perspective. The research informants were four former drug convicts who had been socially reintegrated according to certain criteria. Data collection was carried out using unstructured interviews. Research data was analysed using the interactive model by Miles, Huberman, and Saldana. This study found that the informants use a transcendental-multi-step flow communication model in their image restoration strategies. The messages used by informants in image restoration include the five strategies offered by Benoit. However, corrective action and mortification are important strategies in this case. The corrective action strategy is not just about being "clean" from drugs but also about making positive changes in various aspects, such as relationships, work, and religious practice. Apart from having a cognitive consonance effect, the mortification strategy can also repair damaged relationships. Through corrective action and mortification strategies, former prisoners build an image called the "image of repentance".

Crisis communication for public organizations: Examining Pakistan Railways' use of information technology and social media for image repair

AbstractThis study examines the induction of information technology and the use of image‐repair focused crisis response strategies on social media by Pakistan Railways amid a recent crisis. A mix‐method based content analysis (i.e., qualitative and quantitative) to investigate whether and if so, how Pakistan Railways used Benoit's suggested image restoration strategies on social media to repair its image among customers and in print media. Our results show that Pakistan Railways predominantly used reducing the offensiveness of event (40%), followed by corrective action (34.6%), evasion of responsibility (10.6%), denial (8%) and mortification (6.4%) strategies, respectively. In addition, the use of image‐repair focused crisis response strategies significantly varied by social media platform. An analysis of the publics' emotions found in their online comments reveals that, during the course of the organizational crisis communication, negative public emotions gradually subsided into ambivalent ones; and contrary to a highly negative newspaper coverage tone in the beginning of the crisis, the introduction of the Twitter handle has associated with more positive media coverage afterward. Theoretical and practical implications, especially the need for advancing social‐mediated crisis response effectiveness in developing countries, are discussed.

Study on the image restoration strategy and effect of corporates in crisis situations based on text mining

A corporate's reputation may be significantly impacted by how it handles emergencies. To investigate the effect of different coping strategies on corporate image restoration, we collected 47 representative events of corporates in different industries as well as relevant comments from Weibo. Based on the image restoration theory proposed by Benoit, the effects of different strategies on corporate reputation restoration were analyzed by using sentiment analysis and the topic model. We found that the two strategies of corrective action and mortification can usually better alleviate the negative emotions of the public. On the contrary, if corporates respond with strategies of denial, evading responsibility, or reducing offensiveness, there could be strong feelings of dissatisfaction. The case study of the food industry also finds that even if the effect of alleviating the negative emotions of the public is not significant, an appropriate response could shift the attention of some consumers and to some extent serve the purpose of restoring the corporate reputation.

Scandal maketh the man? The evolution of Hugh Grant and the celebrity confessional

ABSTRACT Following a range of supporting roles in the late 1980s, Hugh Grant’s breakthrough performance in Four Weddings and A Funeral (1994) established him as Britain’s ‘go-to’ romantic lead. And yet, a potentially career-ending sex scandal while on the verge of Hollywood stardom could be considered the making of the man. By analysing press coverage using analytical approaches and frameworks from celebrity studies, this article shows how several flashpoints in Grant’s personal life and subsequent ‘celebrity confessionals’ have been central to Grant’s enduring popularity and evolving star persona. As I argue, scandals across three decades, and subsequent confessionals are mirrored in Grant’s maturing onscreen persona – from commitment-phobic characters, to experimentation with satire and comedy for the American market, to his triumphant return in British biography/dramedies. This article considers Grant’s evolving and unique engagement with the media as a type of ‘reverse confessional’ – where Grant’s confessions subsequently expose the shifting nature of celebrity engagement with the media, and less desirable aspects of the (British) tabloid press. In sum, I contend the reverse narrative mode employed by Grant as an ‘image restoration strategy’ has allowed him to reclaim his own narrative and expose key truths about privacy, press coverage, and contemporary celebrity culture.

Retorika dan Power Relations: Strategi Restorasi Citra Kepolisian Republik Indonesia pada Kasus Ferdy Sambo

This research aimed to identify Indonesian National Police (Polri) strategy in carrying out image restoration in the Ferdy Sambo case. The case of Ferdy Sambo attracted substantial public attention throughout the end of 2022 because it involved members of the National Police in criminal acts. This incident undermined the image and reputation of the National Police as a state apparatus whose function is to maintain security and order. Furthermore, the case of Ferdy Sambo has implications for a communication crisis along with reports in the media that involve many parties as sources so that it brings speculation on the image of the Police. A communication strategy to restore the image was required in crisis communication management, especially in the early period of the crisis in order to maintain the organization's reputation. This research used a qualitative approach with qualitative content analysis as the method. This study used William Benoit's strategy formulation as divided image restoration strategies into five categories: "Denial, Evading Responsibility, Reducing offensiveness of events, Corrective action, and Mortification". The findings showed that the Polri image restoration strategy at the beginning of the Ferdy Sambo case was reducing the offensiveness of the event which consisted of bolstering followed by corrective action, while the combination of strategies practice was bolstering, differentiation, compensation, and corrective action in the post-initial case. The image restoration strategy used in the clarification meeting with Commission III of the DPR RI was to assume the crisis as an accident, bolstering, corrective action and mortification. This study found another strategy in the data as the trait of the qualitative content analysis required interpretation, apart from the strategy described by Benoit, namely hierarchical power at the beginning of the crisis, authoritative support in the post-crisis beginning and continuous improvement in the clarification meeting with Commission III of the DPR RI. The organization's power relations with the public and stakeholders determine the rhetoric and various strategies in crisis communication.

Role identity tactics of CEOs in public apologies on twitter and user sentiments

ABSTRACT The public statements of CEOs (such as apologies) should be periodically evaluated to understand the role identity tactics of the CEOs play in navigating through a crisis. While a CEO may exhibit many distinct role identities, studies on the specific identity that is dominant and activated in a crisis are lacking. Thus, we adopted a deductive, qualitative, and interpretive approach, employing content analysis to examine how 30 CEOs apologised on social media to manage organisational identity. We also used the well-tested and reliable typology of image restoration strategies, along with the Koehnian Framework for Assessing the Ethics of Corporate Apologies as theoretical anchors. The results provided two CEO apology categories (the public relations style or personal style) and four discrete identity apology tactics: Humility, caretaker, problem solver, and defensive. Our findings and role-enactment strategy are relevant to both corporate communication managers and CEOs who wish to be more persuasive in their apologies for faster and more positive results.

Underwater image restoration with Haar wavelet transform and ensemble of triple correction algorithms using Bootstrap aggregation and random forests

This paper presents both a new strategy for traditional underwater image restoration using Haar wavelet transform as well as a new learned model that generates an ensemble of triple correction algorithm labels based on histogram quadrants’ cumulative distribution feature instead of generating pixel intensities. The Haar wavelet transform is our tentative dynamic stretching plan that is applied on the input image and its contrast stretched image to generate the degraded wavelet coefficients which are blended using Gaussian pyramid of the saliency weights to restore the original image. The ensemble of triple corrections exerts three color correction algorithms sequentially on the degraded image for restoration. The ensemble of algorithms entails the superposition effect of the red channel mean shifting, global RGB adaptation, global luminance adaptation, global saturation adaptation, luminance stretching, saturation stretching, contrast stretching, adaptive Gamma correction for red spectrum, even to odd middle intensity transference using look-up table, green to red spectrum transference using histogram equalization, local brightening, Dark Channel Prior, fusion restoration, and our Haar wavelet transform restoration. The source is available at https://github.com/vahidr213/Underwater-Image-Restoration-And-Enhancement-Collection.

Corporate social responsibility disclosures and reputation risk management post the banking royal commission: a study of the big four banks

PurposeThis study aims to explore the use of corporate social responsibility (CSR) disclosures by the “Big Four” Australian banks post the banking royal commission (BRC) to manage their reputational risk.Design/methodology/approachThis paper uses a case study approach through a thematic analysis of the Big Four banks’ annual and sustainability reports and uses reputation risk management (RRM) as a conceptual lens to explore the image restoration strategies used by these banks.FindingsThe study finds that a corrective action strategy was disclosed extensively by all four banks whereby each bank outlined the actions that they were undertaking to correct the deficiencies identified by the BRC. However, the impact of these proposed actions was tampered by the fact that each bank sought to use strategies to reduce the offensiveness of their misdemeanours. It is argued that while disclosure on corrective actions and compensation is useful, an emphasis on reducing offensiveness of actions impacts the effectiveness of banks’ responses and their acceptance of full responsibility for their actions.Research limitations/implicationsThis paper applies the RRM perspective to a recent reputation damaging event, thereby expanding the literature on image restoration strategies used by companies during major incidents.Practical implicationsThis study provides useful insights in relation to the approaches used to manage the reputational risk arising from the BRC. It provides insights into the credibility of information disclosed post an incident and has potential implications for the assurance of such information.Social implicationsGiven the critical importance of the banking industry to modern society, misconduct in this sector needs a closer examination, requiring a greater need for responsibility from its key players.Originality/valueThis study extends the applicability of the RRM perspective to a social incident and highlights that it is reputation, rather than legitimacy, that is critical when organisations in an industry face extensive public scrutiny. A thematic analysis approach adds value to the methods used for analysing CSR disclosures.

Chinese Universities’ Image Repair after Network Public Opinion Events: Strategy Choice and Effect Evaluation

The study aims to address Chinese universities’ image repair strategies after network public opinion events in the field of crisis management; therefore, it takes 43 network public opinion events in Chinese universities as the research object, encodes the official texts issued by universities according to the image restoration strategy, and sums up the image repair strategies commonly used by Chinese universities. Then, natural language processing is used to conduct the sentiment analysis of the online comments obtained. Accordingly, the sentiment index is constructed to evaluate the effect of Chinese universities’ image repair strategies. We find that Chinese universities commonly use the image repair strategy combination of bolstering, provocation, and corrective action; they have not used the apology strategy commonly used in western discourse systems. We also find that the complete information release process has a better image repair effect, particularly in teachers’ lapse and personal safety events. The sentiment index in teachers’ lapse events is the highest and is related to the universities’ corrective actions. The sentiment index in different public opinion hot events is quite different, which may be related to the nature of specific events. In personal safety events, netizens are more satisfied with image repair strategies.

Study on the Recovery Strategy of Tourism in Hubei Province in the Post Epidemic Era

The outbreak and spread of COVID-19 has had a negative impact on the development of China's tourism industry. Wuhan is an early outbreak of COVID-19 in the world and also a region deeply affected by the epidemic. How to repair the image of a tourist destination has become an important issue for the revival and development of domestic tourism at this stage. Based on the actual situation of Wuhan, this paper makes strategic measures to reveal the efforts made by domestic tourism marketing during the COVID-19 epidemic period to maintain the positive image of tourism, and provides reference for the selection and formulation of post-EPIDEMIC tourism destination image restoration strategies.

Underwater image segmentation in the wild using deep learning

Image segmentation is an important step in many computer vision and image processing algorithms. It is often adopted in tasks such as object detection, classification, and tracking. The segmentation of underwater images is a challenging problem as the water and particles present in the water scatter and absorb the light rays. These effects make the application of traditional segmentation methods cumbersome. Besides that, to use the state-of-the-art segmentation methods to face this problem, which are based on deep learning, an underwater image segmentation dataset must be proposed. So, in this paper, we develop a dataset of real underwater images, and some other combinations using simulated data, to allow the training of two of the best deep learning segmentation architectures, aiming to deal with segmentation of underwater images in the wild. In addition to models trained in these datasets, fine-tuning and image restoration strategies are explored too. To do a more meaningful evaluation, all the models are compared in the testing set of real underwater images. We show that methods obtain impressive results, mainly when trained with our real dataset, comparing with manually segmented ground truth, even using a relatively small number of labeled underwater training images.

Image repair during a U.S. Securities and Exchange Commission investigation

AbstractThis paper examines management's image repair strategies present in disclosures noting a firm's involvement in an SEC investigation. This empirical analysis employs a systematic content analysis of managements' 10‐K disclosures released from 2010 through 2019. The sample is drawn from firms identified in SEC accounting and auditing enforcement releases. This research suggests that management's disclosure concerning an SEC investigation commonly focuses on adding positive information to the disclosure (bolstering) and discussing plans to solve the problem. Managers commonly employ multiple image repair tactics within the same 10‐K. These findings have key implications for financial reporting regulators and accounting standards setters concerned with understanding how managers may manipulate disclosures. Investors may also be interested in understanding how company managers attempt to restore the firm's reputation when the firm is undergoing regulatory scrutiny. Further, the findings of this study enhance the knowledge of corporate image restoration strategy. This paper is the first to focus on managements’ use of image repair disclosure strategies when a securities regulator is investigating the firm.