Results 1 to 10 of about 896 (171)

IQA Vision Transformed: A Survey of Transformer Architectures in Perceptual Image Quality Assessment

IEEE Access
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, Imran Fareed Nizami, Farman Ullah, Irfan Hussain   +3 more
doaj   +4 more sources

IE-IQA: Intelligibility Enriched Generalizable No-Reference Image Quality Assessment [PDF]

Frontiers in Neuroscience, 2021
Image quality assessment (IQA) for authentic distortions in the wild is challenging. Though current IQA metrics have achieved decent performance for synthetic distortions, they still cannot be satisfactorily applied to realistic distortions because of the generalization problem.
Leida Li, Hancheng Zhu, Jiansheng Qian   +2 more
exaly   +4 more sources

TTL-IQA: Transitive Transfer Learning Based No-Reference Image Quality Assessment [PDF]

IEEE Transactions on Multimedia, 2021
Image quality assessment (IQA) based on deep learning faces the overfitting problem due to limited training samples available in existing IQA databases. Transfer learning is a plausible solution to the problem, in which the shared features derived from the large-scale Imagenet source domain could be transferred from the original recognition task to the
Fan Li, Hantao Liu, Xiaohan Yang
exaly   +3 more sources

NITS-IQA Database: A New Image Quality Assessment Database

Sensors, 2023
This paper describes a newly-created image database termed as the NITS-IQA database for image quality assessment (IQA). In spite of recently developed IQA databases, which contain a collection of a huge number of images and type of distortions, there is still a lack of new distortion and use of real natural images taken by the camera.
Jayesh Ruikar, Saurabh Chaudhury, Chaudhury Saurabh   +2 more
exaly   +4 more sources

Diagnosis based image quality assessment and enhancement for low dose CT image [PDF]

Frontiers in Radiology
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, B.S. Dhevdharsan, U. Shreya Reddy, J. Joshan Athanesious, S. Kiruthika   +4 more
doaj   +2 more sources

Deep learning-based no-reference image quality assessment framework for Cryptosporidium spp. and Giardia spp. [PDF]

PLoS ONE
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, Heshalini Rajagopal, Norrima Mokhtar, Wan Amirul Wan Mohd Mahiyiddin, Yvonne Ai Lian Lim, Masahiro Iwahashi, Ryosuke Harakawa, Fatimah Ibrahim, Takao Ito   +8 more
doaj   +2 more sources

ARET-IQA: An Aspect-Ratio-Embedded Transformer for Image Quality Assessment

Electronics (Switzerland), 2022
Image quality assessment (IQA) aims to automatically evaluate image perceptual quality by simulating the human visual system, which is an important research topic in the field of image processing and computer vision. Although existing deep-learning-based IQA models have achieved significant success, these IQA models usually require input images with a ...
Jiaqi Zhao, Hancheng Zhu, Wen-Liang Du   +2 more
exaly   +2 more sources

A quality assessment algorithm for no-reference images based on transfer learning [PDF]

PeerJ Computer Science
Image quality assessment (IQA) plays a critical role in automatically detecting and correcting defects in images, thereby enhancing the overall performance of image processing and transmission systems.
Yang Yang, Chang Liu, Hui Wu, Dingguo Yu
doaj   +3 more sources

An image quality assessment algorithm based on ‘global + local’ feature fusion [PDF]

PeerJ Computer Science
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, Norisma Binti Idris, Ainuddin Wahid Abdul Wahab, Dingguo Yu, Chang Liu   +4 more
doaj   +3 more sources

ZEN-IQA: Zero-Shot Explainable and No-Reference Image Quality Assessment With Vision Language Model

IEEE Access
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
doaj   +3 more sources