大视野红外视频的无损压缩基于变形域混合预测
Ya Liu1,2, Rui Zhang3, Yong Zhang1
1Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
本研究介绍了一种高效的无损压缩方法,用于大视野 (FOV) 红外视频,显著提高了19.3x的计算效率,同时保持了高压缩性能.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 视频压缩 视频压缩
背景情况:
- 大视野 (FOV) 红外成像产生了大量的数据集,这给传输和存储带来了挑战.
- 现有的压缩技术在与红外视频应用程序 (如目标检测和遥感) 的高数据量作斗争.
研究的目的:
- 为大型FOV红外视频开发一种高效的无损压缩方法.
- 为了应对红外成像中数据传输和存储的挑战.
主要方法:
- 在转换域中使用离散波纹转换 (DWT) 进行分解的混合预测策略.
- 改进了低延迟多视图高效视频编码 (MV-HEVC) 的低频子带,将背景作为参考视图.
- 对高频组件进行像素智能集群边缘预测和最佳方向预测,以最大限度地减少剩余能量.
主要成果:
- 拟议的方法显著优于主流的视频压缩技术.
- 实现了与MV-HEVC可比的压缩性能.
- 显示计算效率提高了19.3倍.
结论:
- 新的压缩方法为大型FOV红外视频提供了高效的解决方案.
- 混合预测策略有效地平衡了压缩性能和计算速度.
- 这一进步对于需要实时处理大型红外数据集的应用程序至关重要.
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