Efficient No-Reference Quality Assessment and Classification Model for Contrast Distorted Images
, 2018 In this paper, an efficient Minkowski Distance based Metric (MDM) for no-reference (NR) quality assessment of contrast distorted images is proposed. It is shown that higher orders of Minkowski distance and entropy provide accurate quality prediction for ...
Cheriet, Mohamed, Nafchi, Hossein Ziaei
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CSPP-IQA: a multi-scale spatial pyramid pooling-based approach for blind image quality assessment
Neural Computing and Applications, 2022 The traditional image quality assessment (IQA) methods are usually based on convolutional neural networks (CNNs). For these IQA methods using CNNs, limited by the feature size of the fully connected layer, the input image needs be tailored to a pre-defined size, which usually results in destroying the original structure and content of the input image ...
Chen, Jingjing +6 more
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Massive Online Crowdsourced Study of Subjective and Objective Picture Quality
, 2015 Most publicly available image quality databases have been created under highly controlled conditions by introducing graded simulated distortions onto high-quality photographs.
Bovik, Alan C., Ghadiyaram, Deepti
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A Distorted-Image Quality Assessment Algorithm Based on a Sparse Structure and Subjective Perception
MathematicsMost image quality assessment (IQA) algorithms based on sparse representation primarily focus on amplitude information, often overlooking the structural composition of images.
Yang Yang, Chang Liu, Hui Wu, Dingguo Yu
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No Reference Image Quality Assessment based on Multi-Expert Convolutional Neural Networks
IEEE Access, 2018 No Reference (NR) Image Quality Assessment (IQA) algorithm is capable of measuring the quality of distorted images without referencing the original images. This property is of great importance in image processing, compression, and transmission.
Chunling Fan +3 more
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LMM-IQA: Image Quality Assessment for Low-Dose CT Imaging
Low-dose computed tomography (CT) represents a significant improvement in patient safety through lower radiation doses, but increased noise, blur, and contrast loss can diminish diagnostic quality. Therefore, consistency and robustness in image quality assessment become essential for clinical applications. In this study, we propose an LLM-based quality
Celik, Kagan +3 more
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Current Trends and Advances in Image Quality Assessment
Elektronika ir Elektrotechnika, 2019 Image quality assessment (IQA) is one of the constantly active areas of research in computer vision. Starting from the idea of Universal Image Quality Index (UIQI), followed by well-known Structural Similarity (SSIM) and its numerous extensions and ...
Krzysztof Okarma
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A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm. [PDF]
PLoS ONE, 2014 Objective and effective image quality assessment (IQA) is directly related to the application of optical remote sensing images (ORSI). In this study, a new IQA method of standardizing the target object recognition rate (ORR) is presented to reflect ...
Tao Yuan +4 more
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ZEN-IQA: Zero-Shot Explainable and No-Reference Image Quality Assessment With Vision Language Model
IEEE AccessNo-reference image quality assessment (NR-IQA), which aims to estimate the perceptual quality of a degraded image without accessing the corresponding original image, is a key challenge in low-level computer vision.
Takamichi Miyata
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CNN-Based Medical Ultrasound Image Quality Assessment
Complexity, 2021 The quality of ultrasound image is a key information in medical related application. It is also an important index in evaluating the performance of ultrasonic imaging equipment and image processing algorithms.
Siyuan Zhang +5 more
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