Full reference image quality assessment
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Benchmarks
Most implemented
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment
Multiscale structural similarity for image quality assessment
Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption
Foundation Models Boost Low-Level Perceptual Similarity Metrics
Papers
Digital twins enable full-reference quality assessment of photoacoustic image reconstructions
Quantitative comparison of the quality of photoacoustic image reconstruction algorithms remains a major challenge. No-reference image quality measures are often inadequate, but full-reference measures require access to a…
Full reference image quality assessmentFull-Reference Image Quality AssessmentImage Quality AssessmentImage ReconstructionPerceptual Error Logarithm: An Efficient and Effective Analytical Method for Full-Reference Image Quality Assessment
In this paper, we propose a new perceptual analytical method for full-reference image assessment. Techniques used in multimedia applications often introduce distortions, which can significantly degrade image and video …
Full reference image quality assessmentFull-Reference Image Quality AssessmentImage Quality AssessmentToward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption
Full-reference image quality assessment (FR-IQA) generally assumes that reference images are of perfect quality. However, this assumption is flawed due to the sensor and optical limitations of modern imaging systems. Mor…
Full reference image quality assessmentFull-Reference Image Quality AssessmentImage Quality AssessmentSuper-ResolutionBELE: Blur Equivalent Linearized Estimator
In the Full-Reference Image Quality Assessment context, Mean Opinion Score values represent subjective evaluations based on retinal perception, while objective metrics assess the reproduced image on the display. Bridging…
Full reference image quality assessmentFull-Reference Image Quality AssessmentImage Quality AssessmentImage Quality Assessment: Investigating Causal Perceptual Effects with Abductive Counterfactual Inference
Existing full-reference image quality assessment (FR-IQA) methods often fail to capture the complex causal mechanisms that underlie human perceptual responses to image distortions, limiting their ability to generalize ac…
counterfactualCounterfactual InferenceFull reference image quality assessmentFull-Reference Image Quality Assessment+1Image Quality Assessment: Enhancing Perceptual Exploration and Interpretation with Collaborative Feature Refinement and Hausdorff distance
Current full-reference image quality assessment (FR-IQA) methods often fuse features from reference and distorted images, overlooking that color and luminance distortions occur mainly at low frequencies, whereas edge and…
Full reference image quality assessmentFull-Reference Image Quality AssessmentImage Quality Assessment