Search Results for author:
Found 11 papers, 3 papers with code
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss
In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity.
Joint Optimization for SSIM-Based CTU-Level Bit Allocation and Rate Distortion Optimization
However, the MSE-based rate distortion optimization (RDO) was still used in these studies.
Saliency detection based on structural dissimilarity induced by image quality assessment model
Similar to IQA models, the structural dissimilarity is computed based on the correlation of the structural features.
Learn to Evaluate Image Perceptual Quality Blindly from Statistics of Self-similarity
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.
Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index
We present a new effective and efficient IQA model, called gradient magnitude similarity deviation (GMSD).
Ranked #6 on
Image Quality Assessment
on MSU FR VQA Database
Learning without Human Scores for Blind Image Quality Assessment
An interesting question is then: can we learn for effective BIQA without using human scored images?
SSIM-Based CTU-Level Joint Optimal Bit Allocation and Rate Distortion Optimization
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.
A Shift-insensitive Full Reference Image Quality Assessment Model Based on Quadratic Sum of Gradient Magnitude and LOG signals
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.
AutoMO-Mixer: An automated multi-objective Mixer model for balanced, safe and robust prediction in medicine
Accurately identifying patient's status through medical images plays an important role in diagnosis and treatment.
FSIM: A Feature Similarity Index for Image Quality Assessment
Image quality assessment (IQA) aims to use computational models to measure the image quality consistently with subjective evaluations.
Ranked #2 on
Image Quality Assessment
on MSU FR VQA Database
Blind CT Image Quality Assessment Using DDPM-derived Content and Transformer-based Evaluator
Subsequently, the distorted image and dissimilarity map are combined into a multi-channel image, which is inputted into a transformer-based image quality evaluator.
