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- 实验方案
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Noise-Free Rule-Based Fuzzy Image Enhancement
摘要： Different kinds of noises have considerable effects on most of image sensing systems. Suitable image contrast enhancement algorithms can improve contrast or retain detail information while reducing noises as well. Fuzzy representation of an image provides a reliable analysis when inexactness occurred at the gray level values. This paper presents a fuzzy-based novel image contrast enhancement method. Several image quality indices, such as similarity, naturalness, and mean brightness preserving examined and experimentally show the effectiveness of the proposed technique in comparison with well-known image enhancement methods such as histogram equalization and contrast limited adaptive histogram equalization methods.
关键词： Image Robustness and Naturalness,Image Quality Index,Image Enhancement,Fuzzy System
更新于2025-09-23 15:23:52
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Image quality optimization using a narrow vertical detector dental cone-beam CT
摘要： Objectives: To determine the optimised kV setting for a narrow detector cone-beam CT (CBCT) unit. Methods: Clinical (CL) and quantitative (QUANT) evaluations of image quality were performed using an anthropomorphic phantom. Technical (TECH) evaluation was performed with a polymethyl methacrylate phantom. Images were obtained using a PaX-i3D Green CBCT (Vatech, Hwaseong, Korea) device, with a large 21x19 and a medium 12x9 cm field of view, and high-dose (HD– ranging from 85 to 110 kV) and low-dose (LD– ranging from 75 to 95 kV) protocols, totalling four groups (21x19 cm HD, 21x19 cm LD, 12x9 cm HD, 12x9 cm LD). The radiation dose within each group was fixed by adapting the mA according to a predetermined dose-area product. For CL evaluation, three observers assessed images based on overall quality, sharpness, contrast, artefacts, and noise. For QUANT evaluation, mean grey value shift, % increase of standard deviation (SD), % of beam-hardening and contrast-to-noise ratio (CNR) were calculated. For TECH evaluation, segmentation accuracy, CNR, metal artefact SD, metal object area, and sharpness were measured. Representative parameters were chosen for CL, QUANT and TECH evaluations to determine the optimal kV based on biplot graphs. kV values of the same protocol were compared by bootstrapping approach. The ones that had statistical differences with the best kV were considered as worse quality. Results: Overall, kV values within the same group showed similar quality (p>0.05), except for 110 kV in 21x19 cm HD and 85 kV in 12x9 cm HD of CL score; also 85, 90 kV in 21x19 cm HD and 75, 80 kV in 21x19 cm LD of QUANT score which were worse (p<0.05). Conclusion: At a constant dose, low and high kV protocols yield acceptable image quality for a narrow-detector CBCT unit.
关键词： Image Quality,Computed-assisted image analysis,Phantoms,Imaging,Optimization,Cone-beam computed tomography
更新于2025-09-23 15:23:52
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A multi-order derivative feature-based quality assessment model for light field image
摘要： This paper presents an image quality assessment (IQA) model exploring the multi-order derivative feature, called Multi-order Derivative Feature-based Model (MDFM), for evaluating the perceptual quality of light field image (LFI). In our approach, for the input reference and distorted LFIs, the multi-order derivative features are extracted by using the discrete derivative filter to represent the image details in different degrees. Then, the similarities of the extracted derivative features are measured independently. Finally, the weight map is established through the maximum value of the second-order derivative feature of reference and distorted LFIs, which is further utilized to pool the similarity map for generating the final score. Extensive simulation results have demonstrated that the proposed MDFM is more consistent with the perception of the HVS on the evaluation of LFI than the classical and state-of-the-art IQA methods.
关键词： Multi-order derivative feature,Light field image,Image quality assessment
更新于2025-09-23 15:23:52
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Relationship between body habitus and image quality and radiation dose in chest X-ray examinations: A phantom study
摘要： Purpose: To evaluate the influence of being overweight on image quality (IQ), radiation dose and acquisition parameters when undertaking adult chest X-ray (CXR) examinations using routine acquisition protocols. Methods: The Lungman chest phantom, with and without chest plates, was used to simulate the chest region for larger size and average adult patients, respectively. Radiographic acquisitions were conducted using 17 X-ray machines located in eight hospitals using their routine clinical protocols. IQ was assessed using relative visual grading analysis (VGA) and 2 alternative forced choice (2AFC) by six observers. Incident air kerma (IAK) was measured using a solid-state dosimeter. Results: IQ mean (range) scores between the hospitals were 16.2 (12.0–21.3) with a 56.0% difference and 20.9 (14.1–23.6) with a 50.2% difference for the standard and larger size phantoms, respectively. IAK mean (range) scores 63 μGy (19–136 μGy) with a 150% difference and 159 μGy (27–384 μGy) with a 173% difference for the standard and larger size phantoms, respectively. The chest plates had a significant negative impact on IQ (P = 0.001) and lead to an increased in IAK by approximately 50%. Conclusion: Visual measures of IQ and IAK showed large differences between hospitals for standard and larger phantom sizes; differences within the hospitals was lower. Overall, Lungman with chest plates was found to degrade IQ and increase radiation dose by a factor of two. Further optimisation is required especially for the larger sized patient’s imaging protocols for all eight hospitals.
关键词： Overweight,Image quality,Obesity,Adult chest radiography,Dose optimisation,Radiation dose
更新于2025-09-23 15:23:52
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Blind Noisy Image Quality Assessment Using Sub-Band Kurtosis
摘要： Noise that afflicts natural images, regardless of the source, generally disturbs the perception of image quality by introducing a high-frequency random element that, when severe, can mask image content. Except at very low levels, where it may play a purpose, it is annoying. There exist significant statistical differences between distortion-free natural images and noisy images that become evident upon comparing the empirical probability distribution histograms of their discrete wavelet transform (DWT) coefficients. The DWT coefficients of low- or no-noise natural images have leptokurtic, peaky distributions with heavy tails; while noisy images tend to be platykurtic with less peaky distributions and shallower tails. The sample kurtosis is a natural measure of the peakedness and tail weight of the distributions of random variables. Here, we study the efficacy of the sample kurtosis of image wavelet coefficients as a feature driving an extreme learning machine which learns to map kurtosis values into perceptual quality scores. The model is trained and tested on five types of noisy images, including additive white Gaussian noise, additive Gaussian color noise, impulse noise, masked noise, and high-frequency noise from the LIVE, CSIQ, TID2008, and TID2013 image quality databases. The experimental results show that the trained model has better quality evaluation performance on noisy images than existing blind noise assessment models, while also outperforming general-purpose blind and full-reference image quality assessment methods.
关键词： sub-band,discrete wavelet transform (DWT),extreme learning machine (ELM),kurtosis,Blind noisy image quality assessment
更新于2025-09-23 15:23:52
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Comparison of image quality and lesion detection between digital and analog PET/CT
摘要： Objective The purpose of this study was to compare image quality and lesion detection capability between a digital and an analog PET/CT system in oncological patients. Materials and methods One hundred oncological patients (62 men, 38 women; mean age of 65 ± 12 years) were prospectively included from January–June 2018. All patients, who accepted to be scanned by two systems, consecutively underwent a single day, dual imaging protocol (digital and analog PET/CT). Three nuclear medicine physicians evaluated image quality using a 4-point scale (?1, poor; 0, fair; 1, good; 2, excellent) and detection capability by counting the number of lesions with increased radiotracer uptake. Differences were considered significant for a p value <0.05. Results Improved image quality in the digital over the analog system was observed in 54% of the patients (p = 0.05, 95% CI, 44.2–63.5). The percentage of interrater concordance in lesion detection capability between the digital and analog systems was 97%, with an interrater measure agreement of κ = 0.901 (p < 0.0001). Although there was no significant difference in the total number of lesions detected by the two systems (digital: 5.03 ± 10.6 vs. analog: 4.53 ± 10.29; p = 0.7), the digital system detected more lesions in 22 of 83 of PET+ patients (26.5%) (p = 0.05, 95% CI, 17.9–36.7). In these 22 patients, all lesions detected by the digital PET/CT (and not by the analog PET/CT) were < 10 mm. Conclusion Digital PET/CT offers improved image quality and lesion detection capability over the analog PET/CT in oncological patients, and even better for sub-centimeter lesions.
关键词： Analog PET/CT,Digital PET/CT,Image quality,Lesion detection capability
更新于2025-09-23 15:23:52
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Blind Stereoscopic Image Quality Assessment Based on Hierarchical Learning
摘要： We proposed a blind image quality assessment model which used classification and prediction for three-dimensional (3D) image quality assessment (denoted as CAP-3DIQA) that can automatically evaluate the quality of stereoscopic images. First, in the classification stage, the model separated the distorted images into several subsets according to the types of image distortions. This process will assign the images with the same distortion type to the same group. After the classification stage, the classified distorted image set is fed into the image quality predictor that contains five different perceptual channels which predict the image quality score individually. Lastly, we used the regression module of support vector machine to evaluate the final image quality score where the input of the regression model is the combination of five channel's outputs. The model we proposed is tested on three public and popular databases, which are LIVE 3D Image Quality Database Phase I, LIVE 3D Image Quality Database Phase II and MCL 3D Image Quality Database. The experimental results show that our proposed model leads to significant performance improvement on quality prediction for stereoscopic images compared with other existing state-of-the-art quality metrics.
关键词： image quality assessment,stereoscopic images,Hierarchical learning,no reference
更新于2025-09-23 15:23:52
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Blind image quality assessment with hierarchy: Degradation from local structure to deep semantics
摘要： Though blind image quality assessment (BIQA) is highly desired in perceptual-oriented image processing systems, it is extremely difficult to design a reliable BIQA method. With the help of the prior knowledge, the human visual system (HVS) hierarchically perceives the quality degradation during the visual recognition. Inspired by this, we suggest different levels of distortion generate individual degradations on hierarchical features, and propose to consider the degradations on both low and high level features for quality prediction. By mimicking the orientation selectivity (OS) mechanism in the primary visual cortex, an OS based local structure is designed for low-level visual information representation. At the meantime, the deep residual network, which possesses multiple levels for feature integration, is employed to extract the deep semantics for high-level visual content representation. By fusing the local structure and the deep semantics, a hierarchical feature set is acquired. Next, the correlations between the degradations of image qualities and their corresponding hierarchical feature sets are analyzed, and a novel hierarchical feature degradation (HFD) based BIQA (HFD-BIQA) method is built. Experimental results on the legacy and wild image quality assessment databases demonstrate the prediction accuracy of the proposed HFD-BIQA method, and verify that the HFD-BIQA performs highly consistent with the subjective perception.
关键词： Local structure,Deep semantics,Hierarchical feature degradation,Blind image quality assessment
更新于2025-09-23 15:23:52
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Blind Quality Metric for Contrast-Distorted Images Based on Eigendecomposition of Color Histograms
摘要： Although contrast is a major issue in overall quality assessment of an image, existing contrast evaluators with a reasonable performance are currently scarce. Here, we propose a learning-based blind/no-reference (NR) image quality assessment (IQA) model, dubbed Histogram Eigen-Feature based Contrast Score (HEFCS) for evaluating image contrast. This research seeks for the inter-relationship between contrast degradation and relevant image histogram features. We introduce "eigen-histograms", which are the eigenvectors of the set of image patches' histograms. We found that the randomness of image eigen-histograms and the amplitude of corresponding eigenvalues can reliably reflect the changes in image contrast. Employing these characteristics leads to contrast-aware Histogram Eigen-Feature (HEF) vectors, which are used to compute the contrast score through a prediction model trained using support vector regression (SVR). Extensive analysis and cross validation are performed with five contrast relevant image databases, and the HEFCS performance results are compared with a collection of full-reference (FR), reduced-reference (RR) and no-reference measures. Despite its simplicity and low computational complexity, the HEFCS performs better than all competing NR-IQA models, and also stands among the three best-performers of FR and RR models.
关键词： no-reference/blind,image quality assessment (IQA),Contrast distortion,eigen-histogram
更新于2025-09-23 15:23:52
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[Communications in Computer and Information Science] Advances in Signal Processing and Intelligent Recognition Systems Volume 968 (4th International Symposium SIRS 2018, Bangalore, India, September 19–22, 2018, Revised Selected Papers) || Bit-Plane Specific Measures and Its Applications in Analysis of Image Ciphers
摘要： The paper presents bit-plane specific new measures to visualize the extensive statistical detail of an image. We compute the frequency of ones, maximum run length and correlation among rows (columns) in each bit-plane of an image. The computed measures give row-wise and column-wise structural detail at bit-plane level and help an interpreter to analyze given image deeply for its effective interpretation and understanding. In this paper, the application of these measures is shown in cryptography to statistically analyze the image ciphers. The simulation study shows that the proposed measures are very useful and can be applied in various image processing applications for pattern recognition and understanding of visual objects.
关键词： Bit-plane measures,Image cipher,Image analysis,Quantitative measures,Qualitative measures,Image quality measures
更新于2025-09-23 15:22:29