Results 41 to 50 of about 4,189 (182)

On the Application LBP Texture Descriptors and Its Variants for No-Reference Image Quality Assessment

Journal of Imaging, 2018
Automatic assessing the quality of an image is a critical problem for a wide range of applications in the fields of computer vision and image processing. For example, many computer vision applications, such as biometric identification, content retrieval,
Pedro Garcia Freitas, Luísa Peixoto da Eira, Samuel Soares Santos, Mylene Christine Queiroz de Farias   +3 more
doaj   +1 more source

Improved Image Quality Assessment by Utilizing Pre-Trained Architecture Features with Unified Learning Mechanism

Applied Sciences, 2023
The purpose of the no-reference image quality assessment (NR-IQA) is to measure perceived image quality based on subjective judgments; however, due to the lack of a clean reference image, this is a complicated and unresolved challenge.
Jihyoung Ryu
doaj   +1 more source

An Improved DC Recovery Method from AC Coefficients of DCT-Transformed Images [PDF]

, 2010
Motivated by the work of Uehara et al. [1], an improved method to recover DC coefficients from AC coefficients of DCT-transformed images is investigated in this work, which finds applications in cryptanalysis of selective multimedia encryption.
Ahmad, Junaid Jameel, Kuo, C. -C. Jay, Li, Shujun, Saupe, Dietmar   +3 more
core   +2 more sources

Deep learning-driven multi-view multi-task image quality assessment method for chest CT image

BioMedical Engineering OnLine, 2023
Background Chest computed tomography (CT) image quality impacts radiologists’ diagnoses. Pre-diagnostic image quality assessment is essential but labor-intensive and may have human limitations (fatigue, perceptual biases, and cognitive biases).
Jialin Su, Meifang Li, Yongping Lin, Liu Xiong, Caixing Yuan, Zhimin Zhou, Kunlong Yan   +6 more
doaj   +1 more source

Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment

, 2017
We present a deep neural network-based approach to image quality assessment (IQA). The network is trained end-to-end and comprises ten convolutional layers and five pooling layers for feature extraction, and two fully connected layers for regression ...
Bosse, Sebastian, Maniry, Dominique, Müller, Klaus-Robert, Samek, Wojciech, Wiegand, Thomas   +4 more
core   +1 more source

Terahertz Security Image Quality Assessment by No-reference Model Observers

, 2017
To provide the possibility of developing objective image quality assessment (IQA) algorithms for THz security images, we constructed the THz security image database (THSID) including a total of 181 THz security images with the resolution of 127*380.
A Mittal, A Mittal, AJ Fitzgerald, AK Moorthy, BM Fischer, CT Vu, D Suzuki, F Gao, HR Sheikh, J Galbally, J Shi, K Gu, K Gu, K Gu, K Gu, K Hellen-Halme, KA Moldosanov, L Noferini, LS Chow, MA Saad, ND Narvekar, P Sung-Hyeon, PV Vu, W Hanli, W Xue   +24 more
core   +1 more source

TIQA-MRI: Toolbox for Perceptual Image Quality Assessment of Magnetic Resonance Images

SoftwareX
Magnetic Resonance Imaging (MRI) plays a pivotal role in medical diagnostics and research as a non-invasive imaging tool. The accuracy and reliability of clinical evaluations depend heavily on the quality of MRI images, making high-quality imaging ...
Igor Stępień
doaj   +1 more source

End-to-End Image Patch Quality Assessment for Image/Video With Compression Artifacts

IEEE Access, 2020
In this paper, we present an experimental image quality assessment (IQA) method for image/video patches with compression artifacts. Using the High Efficiency Video Coding (HEVC) standard, we create a new database of image patches with compression ...
Tung Thanh Pham, Xiem Van Hoang, Nghia Trung Nguyen, Duong Trieu Dinh, Le Thanh Ha   +4 more
doaj   +1 more source

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu, Xuanyu Zhang, Xiandong Meng, Jian Zhang   +3 more
wiley   +1 more source