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A modular deep learning pipeline for standardised analysis of pelvic ultrasound images for gynaecology

Adams G, Brightmore L, Barcroft J, Cooper N, Timpson A, Saso S, Getreu N, O’Neill HC.   +7 more
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Corrupted Reference Image Quality Assessment of Denoised Images

IEEE Transactions on Image Processing, 2019
We propose corrupted reference image quality assessment (CRIQA), a novel foundation for reasoning about image quality and image denoising problems jointly. In order to assess the visual quality of a processed image relative to an ideal reference image (not provided), we predict the full-reference image quality assessment (FRIQA) scores of denoised ...
Chen Zhang, Keigo Hirakawa, Wu Cheng
exaly   +3 more sources

No-reference quality assessment of deblocked images

Neurocomputing, 2016
JPEG is the most commonly used image compression standard. In practice, JPEG images are easily subject to blocking artifacts at low bit rates. To reduce the blocking artifacts, many deblocking algorithms have been proposed. However, they also introduce certain degree of blur, so the deblocked images contain multiple distortions.
Leida Li, Yu Zhou 0009, Weisi Lin, Jinjian Wu, Xinfeng Zhang 0001, Beijing Chen   +5 more
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Corrupted reference image quality assessment

2012 19th IEEE International Conference on Image Processing, 2012
We propose a foundation for assessing visual quality with “corrupted reference” (CR-QA)-a new quality assessment (QA) paradigm for reasoning about human vision and image restoration problems jointly. The visual quality of a processed image signal is assessed relative to an ideal reference image (not provided) with the help of observed image. This is in
Wu Cheng, Keigo Hirakawa
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No-Reference Image Quality Assessment for Facial Images

2012
Image quality assessment traditionally means the comparison of original image with its distorted version using conventional methods like Mean Square Error (MSE) or Peak Signal to Noise Ratio (PSNR). In case of Blind Quality Evaluation with no prior knowledge about the image, a single parameter becomes insufficient to define the overall image quality ...
Debalina Bhattacharjee, Surya Prakash 0001, Phalguni Gupta   +2 more
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Reduced- and No-Reference Image Quality Assessment

IEEE Signal Processing Magazine, 2011
Recent years have witnessed dramatically increased interest and demand for accurate, easy-to-use, and practical image quality assessment (IQA) and video quality assessment (VQA) tools that can be used to evaluate, control, and improve the perceptual quality of multimedia content in a wide variety of practical multimedia signal acquisition ...
Zhou Wang 0001, Alan C. Bovik
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No-Reference Image Quality Assessment for Contrast Distorted Images

2021
Image contrast distortion is a common type of distortion in digital images. However, there is almost no research on the no-reference image quality assessment (NR-IQA) algorithm for image contrast. Therefore, we propose a histogram-based NR-IQA algorithm for contrast distorted images.
Yiming Zhu, Xianzhi Chen, Shengkui Dai
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No-Reference Fingerprint Image Quality Assessment

2014
Quality of a fingerprint image is assessed to control the registration of poor quality images in the database so that a good accuracy of fingerprint recognition system can be achieved. This paper proposes a quality assessment scheme for digital fingerprint image. It makes use of complete ridge line of a thinned fingerprint image for quality assessment.
Kamlesh Tiwari, Phalguni Gupta
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