Quality Images Research Articles

Kualitas Produk, Citra Merek dan Electronic Word of Mouth terhadap Keputuusan Pembelian Produk EigerKualitas Produk, Citra Merek dan Electronic Word of Mouth terhadap Keputuusan Pembelian Produk Eiger

This research aims to determine the influence of Product Quality (Variable X1), Brand Image (Variable X2) and Electronic Word of Mouth (Variable X3) on purchasing decisions for Eiger products. The method used in this research is quantitative methods. The data collection technique used by researchers in this research is using primary data obtained through distributing questionnaires and literature study. Data analysis techniques start from data preparation, data tabulation to the testing stage. Based on the results of research calculations, multiple linear regression analysis. The coefficient of determination (R2) value can be obtained from the variables product quality (X1), brand image (X2) and electronic word of mouth (X3) which influence 77.2% (0.772) of the product decision (Y), the remaining 22.8 % influenced by other factors outside this research. In conclusion, product quality and brand image have a positive and significant effect on purchasing decisions, while electronic word of mouth has no effect on purchasing decisions Keywords: Brand Image, Electronic Word Of Mouth, Product Quality

Influence of Product Quality, Trust and Brand Image to Wardah's Customer Satisfaction in Batam City

This research aims to examine the influence of product quality, trust and brand image on Wardah customer satisfaction in Batam City. The population used is users who have used Wardah products, but the number is uncertain. So this type of research is quantitative research with a sampling technique using the Lemeshow formula with a total calculation of 100 respondents. Data collection was carried out through distributing questionnaires and data analysis using data quality tests, such as validity tests, reliability tests, and classical assumption tests including normality tests, multicollinearity tests, and heteroscedasticity tests. The influence test uses multiple linear regression analysis and determinant coefficient analysis, while the hypothesis test uses the t test and f test. The results of multiple linear regression analysis show that product quality, trust and brand image significantly influence customer satisfaction, with the product quality variable having an influence of 18.1% on customer satisfaction. Trust has an influence of 35.5% on customer satisfaction. Brand image has an influence of 58.2% on customer satisfaction. Findings in testing the coefficient of determination (R2) show that product quality, trust and brand image together account for 67.2% of the variation in customer satisfaction. Apart from that, testing using the t test and F test shows that product quality, trust and brand image individually and as a whole have a positive and significant influence on Wardah customer satisfaction in Batam City.

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Treatment planning systems at proton-therapy centres entirely use X-ray computed tomography (CT) as primary imaging technique to infer the proton treatment doses to tumour and healthy tissues. However, proton stopping powers in the body, as derived from X-ray images, suffer from important proton-range uncertainties. In order to reduce this uncertainty in range, one could use proton-CT images instead. The main goal of this work is to test the capabilities of a newly-developed proton-CT scanner, based on the use of a set of tracking detectors and a high energy resolution scintillator for the residual energy of the protons. Different custom-made phantoms were positioned at the field of view of the scanner and were irradiated with protons at the CCB proton-therapy center in Krakow. We measured with the phantoms at different angles and produced sinograms that were used to obtain reconstructed images by Filtered Back-Projection. The obtained images were used to determine the capabilities of our scanner in terms of spatial resolution and proton Relative Stopping Power (RSP) mapping and validate its use as proton-CT scanner. The results show that the scanner can produce medium-high quality images, with spatial resolution better than 2 mm in radiography, below 3 mm in tomography and resolving power in the RSP comparable to other state-of-the-art pCT scanners.

Observational signatures of charged rotating traversable wormhole: shadows and light rings with different accretions

In this work, we investigate the optical appearance of qualitatively new observational features of accretion disk images around the charged rotating traversable wormhole (TWH) space-time for different spin, throat, and charge values. To accomplish this, we first consider the Hamilton–Jacobi method to derive the geodesic equations for the motion of photons and study the effects of parameters on the photon orbit in the observer’s sky. We found that each parameter affects the size and shape of the wormhole (WH) shadow and flatness is observed in the shadow because of spin and other parameters. To produce shadow images of sufficient visual quality but within manageable computational times, we adopt the ray-trace procedure and characterize the significant features of light trajectories on the observer’s screen, depending on the interaction between the space-time structure and the accretion disk. In addition, we consider the static spherically symmetric accretion flow model to observe the specific intensity around the traversable WH space-time geometry. It is found that the intensity and positions of the photon ring vary with respect to the involved parameters. In future observation, this type of study may provide a fertile playground to test the nature of compact objects, specifically the WH in the strong-field regime.

Optimizing Experiential Quality to Drive Positive Post-Consumption Behaviours in Kenyan Theme Parks

Experience quality has become increasingly important, particularly for the theme park sector. This is because visitors' post-consumption behaviours are influenced by experiential quality, and this has an impact on theme parks' overall success. There have been studies on the relationship between psychological outcomes such as perceived value, image, experiential satisfaction, and behavioural intentions in theme parks and experience quality; however, most of these studies have focused on the global north. In light of this, this study examines management' and guests' perceptions of experiencing quality, perceived value, and post-consumption behaviours (satisfaction and behavioural intentions) in what are thought to be Kenya's top theme parks. According to the research findings, improving experiential quality is critical for nurturing favourable post-consumption behaviours from both managerial and tourist perspectives. Furthermore, visitors place a premium on cost/affordability, outstanding service, and enjoyable and thrilling encounters as critical components of delivering visitor value and creating quality and memorable experiences. Both managers and guests reported high visitor satisfaction and positive behavioural intentions. The authors suggest that optimising the quality of visitor experiences at theme parks leads to beneficial post-consumption behaviours and overall park success

Two for One-Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform.

Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: "MIX1", combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and "MIX2", combining T1-weighted images and T1ρ mapping (6:38 min). MIXTURE sequences and their reference 2D and 3D TSE counterparts were acquired from ten human cadaveric knee joints at 3.0 T. Contrast, contrast-to-noise ratios, and coefficients of variation were comparatively evaluated using parametric tests. Clinical radiologists (n = 3) assessed diagnostic quality as a function of sequence and anatomic structure using five-point Likert scales and ordinal regression, with a significance level of α = 0.01. MIX1 and MIX2 had at least equal diagnostic quality compared to reference sequences of the same image weighting. Contrast, contrast-to-noise ratios, and coefficients of variation were largely similar for the PD-weighted FS and T1-weighted images. In clinically feasible scan times, MIXTURE sequences yield morphologic, TSE-based images of diagnostic quality and quantitative parameter maps with additional insights on soft tissue composition and ultrastructure.

Pengaruh Kualitas Produk dan Citra Merek terhadap Minat Beli Make Up Wardah (Studi Kasus Pada Mahasiswa Prodi Manajemen Universitas Pendidikan Ganesha)

This test is aimed at analyzing and proving the role of product quality and brand image in the interest in buying Wardah goods. The information used in this test came from students of the management study program at Ganesha University of Education who used Wardah goods as a sample for a total of 85 tests. This test was carried out with the help of the SPSS 26 for windows subprogram. This test uses the independent variables, namely product quality (X1) and brand image (X2) and the dependent variable, namely purchase intention (Y). Before the information is analyzed using multiple linear regression analysis, it is previously proven by a classic assumption test, because the cues for multiple linear regression analysis are free from classical assumptions. the test findings show that (1) product quality plays a positive and substantial role on purchase intention. (2) brand image has a positive and substantial role on purchase intention. (3) product quality and brand image play a substantial role in purchase intention

Pengaruh Kualitas Pelayanan dan Citra Merek terhadap Kepuasan Pelanggan yang menggunakan Produk Ms Glow di Kota Singaraja

The purpose of this research is to determine the influence of service quality and brand image on customer satisfaction among users of ms glow products in Singaraja city, both partially and collectively. The research design used in this study is quantitative causal research. Purposive sampling, a nonstandard technique, was employed for sample selection, which is a probability sampling method. The number of respondents involved in this study is 100 people. The data collection instrument used was a questionnaire, and the analysis method employed was multiple linear regression analysis. The findings of this study are as follows: (1) service quality has a positive and significant impact on customer satisfaction among users of ms glow products in Singaraja city. (2) brand image has a positive and significant influence on customer satisfaction among users of ms glow products in Singaraja city, and (3) service quality and brand image collectively have a significant impact on customer satisfaction among users of ms glow products in Singaraja city.

Ferumoxytol-enhanced MR venography for mapping lower-extremity venous networks and evaluating varicose veins in patients with diabetes.

Comprehensive evaluation of lower-extremity varicose veins (VVs) in patients with diabetes is crucial for treatment strategizing. The study aims to assess the feasibility of using ferumoxytol-enhanced MR venography (FE-MRV) for lower-extremity venous mapping and the detection of VVs in patients with diabetes. As part of a phase II clinical trial of a generic brand of ferumoxytol, documented patients with diabetes were enrolled and underwent FE-MRV on a 3-Τ MRI system. Two observers assessed FE-MRV images for image quality, signal intensity ratio (SIR), perforator (PV) diameter, and luminal signal uniformity in deep-to-superficial venous networks with the assessment of intra- and inter-rater reliability. FE-MRV was used to detect lower-extremity VVs. Eleven patients underwent FE-MRV without adverse events. The average image quality, as scored by the two observers who assessed 275 venous segments, was 3.4 ± 0.6. Two observers strongly agreed on image quality (κ = 0.90) and SIR measurements (interclass correlation coefficient [ICC]: 0.72) and had good agreement on PV diameter (ICC: 0.64). FE-MRV revealed uniform luminal signals in deep and saphenous venous networks (0.13 ± 0.05 vs 0.08 ± 0.03). Below-knee segments exhibited a significantly higher heterogeneity index than above-knee (p = 0.039) segments. Superficial VVs were observed in 55% (12/22)of legs in 64% (7/11)of patients. Calf muscle VVs were present in 64% (14/22)of legs in 9 patients. FE-MRV safely and robustly mapped entire lower-extremity venous networks, enabling the detection and pre-treatment evaluation of both superficial, and deep VVs in patients with diabetes. Ferumoxytol-enhanced magnetic resonance venography offers a "one-stop" imaging strategy for the detection and pre-operative evaluation of both superficial and deep VVs in diabetic patients. Diabetic patients with VVs are at a higher risk of ulcer-related complications. FE-MRV allowed rapid and comprehensive visualization of the lower-limb venous networks and abdominopelvic veins in diabetic patients. This technique allowed for the detection of superficial and deep VVs in diabetic patients before the development of severe peripheral artery disease.

Dynamic Regularized Adaptive Cluster Optimization (DRACO) for Quantitative Cardiac Cine MRI in Complex Arrhythmias.

Irregular cardiac motion can render conventional segmented cine MRI nondiagnostic. Clustering has been proposed for cardiac motion binning and may be optimized for complex arrhythmias. To develop an adaptive cluster optimization method for irregular cardiac motion, and to generate the corresponding time-resolved cine images. Prospective. Thirteen with atrial fibrillation, four with premature ventricular contractions, and one patient in sinus rhythm. Free-running balanced steady state free precession (bSSFP) with sorted golden-step, reference real-time sequence. Each subject underwent both the sorted golden-step bSSFP and the reference Cartesian real-time imaging. Golden-step bSSFP images were reconstructed using the dynamic regularized adaptive cluster optimization (DRACO) method and k-means clustering. Image quality (4-point Likert scale), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), edge sharpness, and ventricular function were assessed. Paired t-tests, Friedman test, regression analysis, Fleiss' Kappa, Bland-Altman analysis. Significance level P < 0.05. The DRACO method had the highest percent of images with scores ≥3 (96% for diastolic frame, 93% for systolic frame, and 93% for multiphase cine) and the percentages were significantly higher compared with both the k-means and real-time methods. Image quality scores, SNR, and CNR were significantly different between DRACO vs. k-means and between DRACO vs. real-time. Cardiac function analysis showed no significant differences between DRACO vs. the reference real-time. DRACO with time-resolved reconstruction generated high quality images and has early promise for quantitative cine cardiac MRI in patients with complex arrhythmias including atrial fibrillation. Stage 2.

Photon-counting computed tomography for paediatric congenital heart defects yields images of high diagnostic quality with low radiation doses at both 70 kV and 90 kV

BackgroundPhoton-counting computed tomography (PCCT) is a new clinical method that may show better diagnostic quality at lower radiation doses than conventional CT.ObjectiveTo investigate the diagnostic quality and radiation dose of paediatric cardiovascular PCCT for diagnosis of congenital heart defects at 70 kV and 90 kV.Materials and methodsThis retrospective assessment included clinical non-gated paediatric PCCT examinations for assessment of congenital heart defects. Radiation doses were recorded, and overall and specific diagnostic quality (1–4) were scored by four paediatric radiologists. Agreement, differences, and trends were assessed by percent rater agreement, intraclass correlation, Mann–Whitney tests, and Jonckheere-Terpstra tests.ResultsSeventy children with congenital heart defects were examined at 70 kV (n = 35; age 2 days–16 years; 63% boys) or 90 kV (n = 35; age 2 days–17 years; 51% boys). All observers gave a median score of 4 (high diagnostic quality) for both 70 kV and 90 kV, with no difference in median values between tube voltages (all P > 0.06). Agreement for overall scores was 66–94% for 70 kV and 60–77% for 90 kV. Agreement for specific scores was 80–97% for 70 kV and 83–89% for 90 kV. Size-dependent dose estimate was 0.68 mGy (0.25–2.02 mGy) for 70 kV and 1.10 mGy (0.58–2.71 mGy; P < 0.001) for 90 kV. Effective dose was 0.30 mSv (0.15–0.82 mSv) for 70 kV and 0.39 mSv (0.22–1.51 mSv; P = 0.01) for 90 kV.ConclusionPaediatric cardiovascular PCCT yields images for congenital heart defects of high diagnostic quality with low radiation dose at both 70 kV and 90 kV.

Adversarial learning-based camera pose-to-image mapping network for synthesizing new view in real indoor environments

Given a new 6DoF camera pose in an indoor environment, we investigate the challenging problem of predicting the view from that pose based on a set of reference RGBD views. Existing explicit or implicit 3D geometry construction methods are computationally expensive, while those based on learning have primarily focused on isolated views of object categories with regular geometric structures. In contrast to the traditional render-inpaint approach for new view synthesis in real indoor environments, we propose a conditional generative adversarial neural network (P2I-NET) that directly predicts the new view from the given pose. P2I-NET learns the conditional distribution of environment images to establish the correspondence between the camera pose and its view, achieved through innovative designs in its architecture and training loss function. Two auxiliary discriminator constraints are incorporated to ensure consistency between the pose of the generated image and that of the corresponding real-world image in both the latent feature space and the real-world pose space. Moreover, a deep convolutional neural network (CNN) is introduced to further reinforce this consistency in the pixel space. Extensive new view synthesis experiments and pose estimation experiments have been conducted on real indoor datasets. The results demonstrate that P2I-NET outperforms a number of strong baseline models based on NeRF. In particular, it is shown that P2I-NET is 40 to 100 times faster than these competitor techniques while producing images of similar quality. The results also reveal that the discriminator in P2I-NET achieves comparable positioning performance to other positioning methods, despite having a smaller model size. Furthermore, we contribute a new publicly available indoor environment dataset containing 22 high resolution RGBD videos where each frame also has accurate camera pose parameters.

Impact of price fairness, service quality, and destination image on tourist loyalty and satisfaction: A case study of Lake Toba, North Sumatra

Tourist loyalty is crucial for enhancing the well-being of local communities in a region. This study aims to investigate how price fairness, service quality, destination image, and tourist facilities directly and indirectly affect tourist loyalty via tourist satisfaction at Lake Toba, North Sumatra. A quantitative method was utilized for this research. The study focused on tourists who visited Lake Toba in 2022, totaling 179,609 individuals. A sample of 280 tourists was selected using an accidental sampling method, where tourists were chosen randomly. The data collection was conducted through questionnaires based on specific indicators for each variable studied. The data was analyzed using the Structural Equation Model (SEM) technique, employing the Partial Least Square (PLS) method. The findings reveal that tourist satisfaction plays a significant role in mediating the impact of price fairness, service quality, destination image, and tourist facilities on loyalty to Lake Toba, both directly and indirectly. The results indicate that price fairness is the most critical factor for tourists when considering returning to Lake Toba. This study suggests that there should be an authority responsible for ensuring price fairness in tourism services and products at Lake Toba to maintain and improve tourist loyalty.

Effect of contrast agent on T2-weighted fat-suppressed imaging and diffusion-weighted imaging in the diagnosis of breast tumors.

Although previous studies have shown that the injection of contrast agents can improve image quality, the specific impact of this on T2-weighted fat-suppressed (T2 FS) and diffusion-weighted imaging (DWI) sequences in the diagnosis of breast cancer remains incompletely understood. In particular, there is insufficient research on how contrast agents affect the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values within these sequences, and how these changes influence the diagnosis of benign and malignant breast tumors. Breast magnetic resonance images (MRI) were obtained from 178 consecutive patients on a 3T scanner. The SNR and CNR of lesions on T2 FS sequence were calculated before and after contrast agent injection and compared. Differences between pre- and post-contrast ADC in identifying different tumor types were compared using the Kruskal-Wallis H-test and the paired comparison test. The accuracy of ADC values between pre- and post-contrast in distinguishing benign and malignant breast masses was assessed using receiver operating characteristic (ROC) curves. The SNR and CNR of T2 FS sequence increased after contrast injection, and especially for invasive cancer and benign tumor, the increase was significant. For DWI, there was a slight increase or decrease of ADC values after contrast injection, but the ADC values before and after contrast had a similar effect in identifying different types of tumors. In the ROC curve analysis for assessing benign and malignant breast tumors, the area under the curve (AUC) before and after contrast showed similar results. Contrast agent injection can improve the SNR and CNR of T2 FS sequence, thus providing higher quality images for the diagnosis of breast lesions. Furthermore, injection of contrast agent had little effect on the ability of ADC values to identify different types of lesions and both ADC values before and after the contrast agent were able to distinguish between benign and malignant tumors with almost the same accuracy.

BBMS: Investigation to Single Colour Image Visibility Improvement in Turbid Media through Biorthogonal Wavelet Based Depth-map Estimation

Electronic imaging needs good quality, high resolution (HR) digital images for highlighting finer details of the image. Normally images captured by ordinary digital camera are post pro cessed with available software instead of high cost CMOS sensor phased camera. Problem commonly faced with these images may get degraded due to the scattering media which deteriorates contrast, shifts colour, and make overall image whitish. Information from the distant objects suffer from poor medium transmission as well as noise amplification. Biorthogonal wavelet denoising (BWD), compress sparsely in frequency -time space, removes noise from depth estimation and makes the transmission smooth. Moreover, single image recovery is a serious challenge and ill posed problem. The recovered image improves compare to degraded image significantly and dis cards possibility of false edge detection as well as prevent colour shift and low contrast. Good quality images are found with objective evaluation. Moreover, different wavelets, thresholds, and decomposition levels have been studied and compared. Time complexity is linear due to wavelet domain analysis which makes the technique fast, reliable, and visually pleasing.

Influence of Service Quality and Brand Image on Customer Satisfacation at BMR Tour And Travel Agent

Tourism development is increasingly rapid with many increasing tourism trends. The increasing development of tourism causes an increase in demand for tours usually carried out by Tour and Travel, with this increase the quality of service and brand image is needed to produce customer satisfaction. This research uses descriptive quantitative methods to determine the magnitude of the influence of variables (X), namely Service Quality and Brand Image and variable (Y), namely Customer Satisfaction, using a regression research design. The data obtained by 30 respondents was then tabulated and analyzed using multiple linear regression tests using the SPSS version 22.0 program. The results of the research on the influence of service quality and brand image on customer satisfaction showed that the F-test results obtained were an F count of 55,523, which states that all Service Quality and Brand Image variables simultaneously and significantly influence the dependent variable (Customer Satisfaction).

The Influence Of Product Quality And Brand Image On Purchase Decision Of Indosat Card Users With Customer Trust As An Intervening Variable (Case Study of Economics Faculty Students University Sarjanawiyata Tamansiswa Yogyakarta)

The aim of this research is to test and explain the influence of product quality and brand image on Indosat card users' purchase decisions with customer trust as an intervening variable. This research was conducted on students at the Faculty of Economics, Bachelorwiyata Tamansiswa University using the Slovin formula with a sample size of 100 respondents who used statements each variable via Google from to share with students. The research results show that product quality has a positive and significant influence on customer trust, the influence of brand image has a positive and significant influence on customer trust, product quality has no significant influence on purchase decisions, brand image has a positive and significant influence on purchase decisions, and customer trust has a positive and significant influence. significant impact on purchase decisions.

Hybrid U-Net and Swin-transformer network for limited-angle cardiac computed tomography

Objective. Cardiac computed tomography (CT) is widely used for diagnosis of cardiovascular disease, the leading cause of morbidity and mortality in the world. Diagnostic performance depends strongly on the temporal resolution of the CT images. To image the beating heart, one can reduce the scanning time by acquiring limited-angle projections. However, this leads to increased image noise and limited-angle-related artifacts. The goal of this paper is to reconstruct high quality cardiac CT images from limited-angle projections. Approach. The ability to reconstruct high quality images from limited-angle projections is highly desirable and remains a major challenge. With the development of deep learning networks, such as U-Net and transformer networks, progresses have been reached on image reconstruction and processing. Here we propose a hybrid model based on the U-Net and Swin-transformer (U-Swin) networks. The U-Net has the potential to restore structural information due to missing projection data and related artifacts, then the Swin-transformer can gather a detailed global feature distribution. Main results. Using synthetic XCAT and clinical cardiac COCA datasets, we demonstrate that our proposed method outperforms the state-of-the-art deep learning-based methods. Significance. It has a great potential to freeze the beating heart with a higher temporal resolution.

An effective transformer based on dual attention fusion for underwater image enhancement

Underwater images suffer from color shift, low contrast, and blurred details as a result of the absorption and scattering of light in the water. Degraded quality images can significantly interfere with underwater vision tasks. The existing data-driven based underwater image enhancement methods fail to sufficiently consider the impact related to the inconsistent attenuation of spatial areas and the degradation of color channel information. In addition, the dataset used for model training is small in scale and monotonous in the scene. Therefore, our approach solves the problem from two aspects of the network architecture design and the training dataset. We proposed a fusion attention block that integrate the non-local modeling ability of the Swin Transformer block into the local modeling ability of the residual convolution layer. Importantly, it can adaptively fuse non-local and local features carrying channel attention. Moreover, we synthesize underwater images with multiple water body types and different degradations using the underwater imaging model and adjusting the degradation parameters. There are also perceptual loss functions introduced to improve image vision. Experiments on synthetic and real-world underwater images have shown that our method is superior. Thus, our network is suitable for practical applications.

De-occlusion and recognition of frontal face images: a comparative study of multiple imputation methods

AbstractIncreasingly, automatic face recognition algorithms have become necessary with the development and extensive use of face recognition technology, particularly in the era of machine learning and artificial intelligence. However, the presence of unconstrained environmental conditions degrades the quality of acquired face images and may deteriorate the performance of many classical face recognition algorithms. Due to this backdrop, many researchers have given considerable attention to image restoration and enhancement mechanisms, but with minimal focus on occlusion-related and multiple-constrained problems. Although occlusion robust face recognition modules, via sparse representation have been explored, they require a large number of features to achieve correct computations and to maximize robustness to occlusions. Therefore, such an approach may become deficient in the presence of random occlusions of relatively moderate magnitude. This study assesses the robustness of Principal Component Analysis and Singular Value Decomposition using Discrete Wavelet Transformation for preprocessing and city block distance for classification (DWT-PCA/SVD-L1) face recognition module to image degradations due to random occlusions of varying magnitudes (10% and 20%) in test images acquired with varying expressions. Numerical evaluation of the performance of the DWT-PCA/SVD-L1 face recognition module showed that the use of the de-occluded faces for recognition enhanced significantly the performance of the study recognition module at each level (10% and 20%) of occlusion. The algorithm attained the highest recognition rate of 85.94% and 78.65% at 10% and 20% occlusions respectively, when the MICE de-occluded face images were used for recognition. With the exception of Entropy where MICE de-occluded face images attained the highest average value, the MICE and RegEM result in images of similar quality as measured by their Absolute mean brightness error (AMBE) and peak signal to noise ratio (PSNR). The study therefore recommends MICE as a suitable imputation mechanism for de-occlusion of face images acquired under varying expressions.