Search Results for author: Xuanqin Mou

Found 9 papers, 4 papers with code

AutoMO-Mixer: An automated multi-objective Mixer model for balanced, safe and robust prediction in medicine

no code implementations4 Mar 2022 Xi Chen, Jiahuan Lv, Dehua Feng, Xuanqin Mou, Ling Bai, Shu Zhang, Zhiguo Zhou

Accurately identifying patient's status through medical images plays an important role in diagnosis and treatment.

A Shift-insensitive Full Reference Image Quality Assessment Model Based on Quadratic Sum of Gradient Magnitude and LOG signals

no code implementations21 Dec 2020 Congmin Chen, Xuanqin Mou

In this paper, we propose an FR-IQA model with the quadratic sum of the GM and the LOG signals, which obtains good performance in image quality estimation considering shift-insensitive property for not well-registered reference and distortion image pairs.

Image Quality Assessment Image Quality Estimation +1

SSIM-Based CTU-Level Joint Optimal Bit Allocation and Rate Distortion Optimization

no code implementations28 Apr 2020 Yang Li, Xuanqin Mou

This problem is due to the lack of an accurate R-$D_\text{SSIM}$ model that can be used uniformly in both OBA and RDO.


Saliency detection based on structural dissimilarity induced by image quality assessment model

1 code implementation24 May 2019 Yang Li, Xuanqin Mou

Similar to IQA models, the structural dissimilarity is computed based on the correlation of the structural features.

Image Quality Assessment Saliency Detection

Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

9 code implementations3 Aug 2017 Qingsong Yang, Pingkun Yan, Yanbo Zhang, Hengyong Yu, Yongyi Shi, Xuanqin Mou, Mannudeep K. Kalra, Ge Wang

In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity.

Image Denoising

Learn to Evaluate Image Perceptual Quality Blindly from Statistics of Self-similarity

no code implementations10 Oct 2015 Wufeng Xue, Xuanqin Mou, Lei Zhang

Among the various image quality assessment (IQA) tasks, blind IQA (BIQA) is particularly challenging due to the absence of knowledge about the reference image and distortion type.

Image Quality Assessment

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