ZEN-IQA: Zero-Shot Explainable and No-Reference Image Quality Assessment With Vision Language Model
No-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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IQA Vision Transformed: A Survey of Transformer Architectures in Perceptual Image Quality Assessment
In an era dominated by visual content, perceptual image quality assessment (IQA) is crucial for enhancing user experiences and driving technological advancements across various domains.
Mobeen Ur Rehman +3 more
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Diagnosis based image quality assessment and enhancement for low dose CT image [PDF]
Low-dose Computed Tomography (CT) imaging minimizes radiation exposure but often results in degraded image quality, making diagnosis challenging. Image Quality Assessment (IQA) is a process of quantitatively evaluating the visual quality of images and ...
B. Nirupama +4 more
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On optimisation of Paganin's method for propagation-based X-ray phase-contrast imaging and tomography. [PDF]
Abstract Paganin's method for image reconstruction in propagation‐based phase‐contrast X‐ray imaging and tomography has enjoyed broad acceptance in recent years, with over one thousand publications citing its use. The present paper discusses approaches to optimisation of the method with respect to simple image quality metrics, such as signal‐to‐noise ...
Gureyev TE +3 more
europepmc +2 more sources
Deep learning-based no-reference image quality assessment framework for Cryptosporidium spp. and Giardia spp. [PDF]
Image Quality Assessment (IQA) plays a critical role in image-based decision-making systems, especially in domains requiring high diagnostic precision. Effective feature information is a prerequisite for the high performance of machine learning methods ...
Muhammad Amirul Aiman Asri +8 more
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An image quality assessment algorithm based on ‘global + local’ feature fusion [PDF]
Recently, there has been increasing research on image quality assessment. Among the existing mainstream approaches, image feature extraction tends to be simplistic, leading to insufficient quality information extraction and underutilization of the ...
Yang Yang +4 more
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No-Reference Image Quality Assessment Model Based on Generated Perceptual Difference [PDF]
The visual perception difference in the Human Visual System(HVS) is key to image quality evaluation.By sensing the visual difference between the distorted image and the reference image,the distortion degree of the image can be judged.However,this method ...
LIU Hai, YANG Huan, PAN Zhenkuan, HUANG Baoxiang, HOU Guojia
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TIQA-PSI: Toolbox for perceptual Image Quality Assessment of Pan-Sharpened Images
A Pan-Sharpening (PS) technique integrates spatial details of a high-resolution panchromatic (PAN) image with spectral information of a low-resolution multi-spectral (MS) image, creating a single high-resolution color image.
Igor Stępień, Mariusz Oszust
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No-Reference Image Quality Assessment Based on Dual-Domain Feature Fusion
Image quality assessment (IQA) aims to devise computational models to evaluate image quality in a perceptually consistent manner. In this paper, a novel no-reference image quality assessment model based on dual-domain feature fusion is proposed, dubbed ...
Yueli Cui
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Given the reference (distortion-free) image, full-reference image quality assessment (FR-IQA) algorithms seek to assess the perceptual quality of the test image.
Domonkos Varga
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