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全合一变压器用于在恶劣天气下进行图像恢复
IEEE transactions on pattern analysis and machine intelligence
|January 28, 2026
概括
这项研究介绍了AllRestorer,这是一种用于恢复多个恶劣天气条件 (如低光,雾,雨和雪) 损坏的图像的新框架. 它通过同时适应性地处理所有损伤来实现卓越的恢复,显著提高图像质量.
科学领域:
- 计算机视觉 计算机视觉
- 图像恢复 图像恢复
- 人工智能的人工智能
背景情况:
- 在现实世界中,恶劣的天气条件会同时导致多个图像退化.
- 现有的图像修复模型由于依赖场景描述器而难以准确地区分和处理复合材料的退化.
- 这种限制导致在需要强大的图像恢复的实际应用中性能不足.
研究的目的:
- 提出一种新的基于变压器的恢复框架,AllRestorer,能够适应多次恶劣天气损害.
- 克服现有方法的局限性,这些方法专注于单一或有限的复合材料降解.
- 为了提高复杂的,现实世界的天气条件下图像恢复的准确性和有效性.
主要方法:
- 开发了AllRestorer,这是一个基于变压器的框架,旨在同时恢复低光,雾,雨和雪损害.
- 引入了全合一变压器块 (AiOTB),使单个图像中的多个降解能够进行自适应处理.
- 在AiOTB中使用复合场景嵌入 (图像和文本嵌入) 和自适应性降解权重,用于精确的恢复控制.
主要成果:
- AllRestorer 适应性地考虑了所有天气障碍,避免了不准确的场景描述器的误导.
- 全合一变压器块 (AiOTB) 可以有效地同时处理多个降解,性能优于单个降解变压器.
- 与基线方法相比,CDD-11数据集的峰值信号噪声比率 (PSNR) 显著增加5.00dB.
结论:
- AllRestorer提供了一个强大的解决方案,用于重复恶劣天气的图像,通过适应性地解决多个同时的退化.
- 拟议的AiOTB和复合场景嵌入为提高修复准确性和控制提供了一种新的方法.
- 这一框架表明,在具有挑战性的环境条件下处理复杂的图像恢复任务方面取得了重大进展.
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