Results 81 to 90 of about 4,120 (175)
Subjective and Objective Quality Assessment of Image: A Survey
Majlesi Journal of Electrical EngineeringWith the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. Measuring the image quality is of fundamental importance for numerous image processing applications, where the ...
Pedram Mohammadi +2 more
doaj
No-Reference Image Quality Assessment Based on Multi-Task Generative Adversarial Network
IEEE Access, 2019 Since human observers are the ultimate receivers of an image, most of the image quality assessment (IQA) methods are based on analysis of the properties and mechanism of the human visual system.
Yao Ma +3 more
doaj +1 more source
Grounding-IQA: Multimodal Language Grounding Model for Image Quality Assessment
The development of multimodal large language models (MLLMs) enables the evaluation of image quality through natural language descriptions. This advancement allows for more detailed assessments. However, these MLLM-based IQA methods primarily rely on general contextual descriptions, sometimes limiting fine-grained quality assessment.
Zheng Chen, Yulun Zhang
openaire +1 more source
Refine-IQA: Multi-Stage Reinforcement Finetuning for Perceptual Image Quality Assessment
Reinforcement fine-tuning (RFT) is a proliferating paradigm for LMM training. Analogous to high-level reasoning tasks, RFT is similarly applicable to low-level vision domains, including image quality assessment (IQA). Existing RFT-based IQA methods typically use rule-based output rewards to verify the model's rollouts but provide no reward supervision ...
Jia, Ziheng +4 more
openaire +2 more sources
LAR-IQA: A Lightweight, Accurate, and Robust No-Reference Image Quality Assessment Model
Recent advancements in the field of No-Reference Image Quality Assessment (NR-IQA) using deep learning techniques demonstrate high performance across multiple open-source datasets. However, such models are typically very large and complex making them not so suitable for real-world deployment, especially on resource- and battery-constrained mobile ...
Nasim Jamshidi Avanaki +3 more
openaire +2 more sources
Charting the path forward: CT image quality assessment - an in-depth review
Journal of King Saud University: Computer and Information SciencesComputed Tomography (CT) is a frequently utilized imaging technology that is employed in the clinical diagnosis of many disorders. However, clinical diagnosis, data storage, and management are faced with significant challenges posed by a huge volume of ...
Siyi Xun +8 more
doaj +1 more source
IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models
Visual Computing for Industry, Biomedicine, and ArtLarge language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich
Zhihao Chen +6 more
doaj +1 more source
MS-IQA: A Multi-scale Feature Fusion Network for PET/CT Image Quality Assessment
Accepted to MICCAI ...
Li, Siqiao +9 more
openaire +2 more sources
Dog-IQA: Standard-guided Zero-shot MLLM for Mix-grained Image Quality Assessment
Image quality assessment (IQA) serves as the golden standard for all models' performance in nearly all computer vision fields. However, it still suffers from poor out-of-distribution generalization ability and expensive training costs. To address these problems, we propose Dog-IQA, a standard-guided zero-shot mix-grained IQA method, which is training ...
Liu, Kai +7 more
openaire +2 more sources
DP-IQA: Utilizing Diffusion Prior for Blind Image Quality Assessment in the Wild
Blind image quality assessment (IQA) in the wild, which assesses the quality of images with complex authentic distortions and no reference images, presents significant challenges. Given the difficulty in collecting large-scale training data, leveraging limited data to develop a model with strong generalization remains an open problem.
Fu, Honghao +4 more
openaire +2 more sources