Installs into .claude/skills of the current project.
Are you the author of Fusion Quality Metrics?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-fusion-quality-metrics)
---
name: fusion_quality_metrics
description: Compute deterministic no-reference proxy metrics for fused infrared-visible images, including entropy, contrast, edge preservation, and stability.
---
# Fusion Quality Metrics
## When To Use
Use this skill for bounded infrared-visible image-fusion analysis derived from `arXiv:2206.09581`, especially when preserving modality-specific features, comparing explicit/implicit mechanisms, or running proxy recovery.
## Inputs
See the corresponding module document in the attempt directory. Inputs must be local text or numeric arrays; do not read any original paper repository.
## Outputs
The skill returns deterministic JSON-compatible diagnostics suitable for downstream recovery and analysis.
## Workflow
1. Validate input shapes or text content.
2. Execute the module-specific mechanism with deterministic defaults.
3. Return compact evidence and numeric diagnostics.
4. For recovery, keep proxy/reduced labels explicit.
## Validation
Run `python /share/project/yuyang/workspace/Paper2Skills/Paper2Skills-Agent/src/packages/paper2skills-agent/src/paper2skills/skills/module-to-skill/scripts/validate_skill_tree.py /share/project/yuyang/workspace/Paperbench/record/case13/extracted_skills_attempt_001/exorl_unsupervised_rl/fusion_quality_metrics --run-tests`.
## Limitations
This skill implements a lightweight, reusable proxy for the paper mechanism, not the full 21-test-set benchmark from the paper.
