- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Rectangular-Normalized Superpixel Entropy Index for Image Quality Assessment
摘要： Image quality assessment (IQA) is a fundamental problem in image processing that aims to measure the objective quality of a distorted image. Traditional full-reference (FR) IQA methods use fixed-size sliding windows to obtain structure information but ignore the variable spatial configuration information. In order to better measure the multi-scale objects, we propose a novel IQA method, named RSEI, based on the perspective of the variable receptive field and information entropy. First, we find that consistence relationship exists between the information fidelity and human visual of individuals. Thus, we reproduce the human visual system (HVS) to semantically divide the image into multiple patches via rectangular-normalized superpixel segmentation. Then the weights of each image patches are adaptively calculated via their information volume. We verify the effectiveness of RSEI by applying it to data from the TID2008 database and denoise algorithms. Experiments show that RSEI outperforms some state-of-the-art IQA algorithms, including visual information fidelity (VIF) and weighted average deep image quality measure (WaDIQaM).
关键词： image quality assessment,superpixel segmentation,mutual information
更新于2025-09-23 15:22:29
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Quality Assessment of 3D Synthesized Images via Measuring Local Feature Similarity and Global Sharpness
摘要： Depth-Image-Based Rendering (DIBR) techniques can be used to generate virtual views for free-viewpoint video (FVV) application. However, the DIBR algorithms will introduce geometric distortions that mainly distribute at the disoccluded regions in the synthesized views. It has been demonstrated that conventional 2D quality metrics are not suitable for the synthesized views. In this paper, we propose a new quality model for 3D synthesized images by measuring the block-wise texture similarity and color contrast similarity in critical areas, and global gradient magnitude deviation. A critical area detection module is first employed using a warping method with morphological operation. Then, the critical areas are partitioned into blocks, which are classified as edge blocks, texture blocks, and smooth blocks by computing discrete cosine transform coefficient values. Block-wise texture similarity and color contrast similarity in the corresponding areas are calculated, which are weighted by the size of critical areas. Furthermore, gradient magnitude deviation is measured to quantify global sharpness. Finally, the two scores are pooled to obtain the overall quality. Experimental results on IRCCyN/IVC, IETR and MCL-3D DIBR image databases indicate that our method achieves higher quality prediction accuracy than the state-of-the-art quality metrics.
关键词： view synthesis,Quality assessment,3D synthesized image,Depth-Image-Based Rendering
更新于2025-09-23 15:22:29
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[IEEE ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Calgary, AB (2018.4.15-2018.4.20)] 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - No-Reference Hdr Image Quality Assessment Method Based on Tensor Space
摘要： The full-reference image quality assessment (IQA) method are limited in practical applications. Here we propose a no-reference quality assessment method for high dynamic range (HDR) images based on tensor space. First, the tensor decomposition is used to generate three feature maps of an HDR image, considering color and structure information of the HDR image. Second, for a given HDR image, the corresponding multi-scale manifold structure features are extracted from the first feature map. For the second and third feature maps of the HDR image, multi-scale contrast features are extracted. Finally, the extracted features are aggregated by support vector regression to obtain the objective quality score of the HDR image. Experimental results show that the proposed method is superior to some representative full and no-reference methods, and even superior to the full-reference HDR IQA method, HDR-VDP-2.2, on the Nantes database. The proposed method has a higher consistency with human visual perception.
关键词： high dynamic range,feature maps,No-reference,image quality assessment,tensor space
更新于2025-09-23 15:22:29
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[ACM Press the 3rd International Conference - Seoul, Republic of Korea (2018.08.22-2018.08.24)] Proceedings of the 3rd International Conference on Biomedical Signal and Image Processing - ICBIP '18 - Noise and Resolution Performance Evaluation for Statistical and Non-Statistical Iterative CBCT Reconstruction Methods
摘要： Non-statistical iterative and statistical iterative reconstruction (SIR) methods establish different models for Cone-beam computed tomography (CBCT) image reconstruction, which possibly produce different performance outcomes in reconstructed images. This paper presents a method to evaluate the noise and resolution properties of statistical and non-statistical iterative conditions. An algorithms EGSnrc/BEAMnrc Monte Carlo (MC) system was built for generating CBCT projections of a digital water phantom. SIR based OSC-TV (ordered subsets convex via total variation minimization) algorithm was selected to compare with non-statistical ASD-POCS (adaptive steepest descent-projection onto convex sets) algorithm and conventional FDK algorithm. The results demonstrate that ASD-POCS algorithm achieved a higher modulation transfer function than SIR based OSC-TV algorithm at the price of a higher image noise, while OSC-TV algorithm yielded best noise equivalent quanta performance among the three algorithms. The results of our study could guide a better evaluation and optimization of reconstruction algorithms for CBCT imaging.
关键词： Noise equivalent quanta,Image quality assessment,Noise power spectrum,Modulation transfer function,Computed tomography
更新于2025-09-23 15:22:29
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No-reference image quality assessment using gradient magnitude and wiener filtered wavelet features
摘要： No-reference image quality assessment (NR-IQA) aims to evaluate the perceived quality of distorted images without prior knowledge of pristine version of the images. The quality score is predicted based on the features extracted from the distorted image, which needs to correlate with the mean opinion score. The prediction of an image quality score becomes a trivial task, if the noise affecting the quality of an image can be modeled. In this paper, gradient magnitude and Wiener filtered discrete wavelet coefficients are utilized for image quality assessment. In order to reconstruct an estimated noise image, Wiener filter is applied to discrete wavelet coefficients. The estimated noise image and the gradient magnitude are modeled as conditional Gaussian random variables. Joint adaptive normalization is applied to the conditional random distribution of the estimated noise image and the gradient magnitude to form a feature vector. The feature vector is used as an input to a pre-trained support vector regression model to predict the image quality score. The proposed NR-IQA is tested on five commonly used image quality assessment databases and shows better performance as compared to the existing NR-IQA techniques. The experimental results show that the proposed technique is robust and has good generalization ability. Moreover, it also shows good performance when training is performed on images from one database and testing is performed on images from another database.
关键词： Wiener filtering,Gradient magnitude,Discrete wavelet transform,No-reference image quality assessment
更新于2025-09-23 15:21:21
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Rapid quality assessment of isogams using laser plasma spectroscopy
摘要： In this paper, the quality assessment of isogams is demonstrated by laser-induced breakdown spectroscopy (LIBS) using the comparative standardization method. Here, the mass concentrations of carbon and hydrogen, as basic elements of tar, relative to that of calcium, as an undesired element, are taken into account as principal parameters to determine the quality of isogams. Hence, the intensity ratios of H?? line of hydrogen (656.28?nm), the (0, 0) band of CN (388.34?nm), and the (0, 0) band of C2 (516.52?nm) to the line intensity of once-ionized calcium (317.93?nm) are considered as determinant markers for five different pre-known isogam brands. Qualitatively, classification of the isogams based on this approach is in full agreement with that obtained from the results of Fourier-transform infrared (FTIR) spectroscopy. In FTIR spectra, two stronger transitions of 2849?cm?1 and 2917?cm?1 related to the symmetric and asymmetric stretching vibrations of C–H play the principal role in the analysis of samples. Furthermore, the results obtained from energy-dispersive X-ray (EDX) analysis quantitatively confirm the LIBS outcomes. And finally, to reveal the differences between isogams from various aspects, the linear discriminant analysis (LDA) is exploited as a statistical approach.
关键词： FTIR spectroscopy,EDX analysis,Linear discriminant analysis (LDA),Laser-induced breakdown spectroscopy (LIBS),Isogams,Quality assessment
更新于2025-09-23 15:21:01
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Large Scale Subjective Video Quality Study
摘要： Most of today’s video quality assessment (VQA) databases contain very limited content and distortion diversities and fail to adequately represent real world video impairments. This is in part because conducting subjective studies in the lab is slow, inefficient and expensive process. Crowdsourcing quality scores is a more scalable solution. However given that viewers operate under innumerable viewing conditions (including display resolutions, viewing distances, internet connection speeds) and because they are not closely supervised, multiple technical challenges arise. We carefully designed a framework in Amazon Mechanical Turk (AMT) to address the many technical issues that are faced. We launched the largest available VQA study, collecting more than 205000 opinion scores provided by more than 4700 unique participants. We have verified that our framework provided us with results that are highly consistent with the ones obtained in a lab environment under controlled conditions.
关键词： Subjective Study,Video Quality Assessment,Crowdsourcing
更新于2025-09-23 15:21:01
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Convolutional Neural Network for Blind Mesh Visual Quality Assessment Using 3D Visual Saliency
摘要： In this work, we propose a convolutional neural network (CNN) framework to estimate the perceived visual quality of 3D meshes without having access to the reference. The proposed CNN architecture is fed by small patches selected carefully according to their level of saliency. To do so, the visual saliency of the 3D mesh is computed, then we render 2D projections from the 3D mesh and its corresponding 3D saliency map. Afterward, the obtained views are split to obtain 2D small patches that pass through a saliency filter to select the most relevant patches. Experiments are conducted on two MVQ assessment databases, and the results show that the trained CNN achieves good rates in terms of correlation with human judgment.
关键词： blind mesh visual quality assessment,Convolutional neural network (CNN),mesh visual saliency
更新于2025-09-23 15:21:01
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Image quality assessment method based on relation intensity and details similarity
摘要： In this paper, we present an e?ective quality assessment method based on the relation intensity ratio and detail similarity for image quality assessment (IQA) with the full reference image, which ?rst allows us to compute the nonlinear gradient magnitude with Gaussian smoothing of the reference and distorted images and construct the relation intensity ratio and detail similarity between them. Next, the ?nal IQA map is formed by linearly combining the relation intensity ratio with the detail similarity. Finally, we adopt a new pooling strategy which e?ectively integrates the mean and standard deviation of the ?nal IQA map to accurately predict image quality. Experiments based on two publicly available databases show that the proposed method can provide accurate predictions compared with most state-of-the-art IQA methods.
关键词： detail similarity,relation intensity ratio,Image quality assessment
更新于2025-09-23 15:21:01
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2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges
摘要： Image quality is important not only for the viewing experience, but also for the performance of image processing algorithms. Image quality assessment (IQA) has been a topic of intense research in the fields of image processing and computer vision. In this paper, we first analyze the factors that affect two-dimensional (2D) and three-dimensional (3D) image quality, and then provide an up-to-date overview on IQA for each main factor. The main factors that affect 2D image quality are fidelity and aesthetics. Another main factor that affects stereoscopic 3D image quality is visual comfort. We also describe the IQA databases and give the experimental results on representative IQA metrics. Finally, we discuss the challenges for IQA, including the influence of different factors on each other, the performance of IQA metrics in real applications, and the combination of quality assessment, restoration, and enhancement.
关键词： image aesthetics assessment,visual comfort,Image quality assessment,and image quality enhancement.
更新于2025-09-23 15:19:57