学习可控制的ISP用于图像增强
概括
可控制的图像信号处理器 (CRISP) 通过有效地控制各种风格的ISP参数来增强图像. 这种方法实现了高质量和风格控制,比之前的工作要少得多的参数和计算.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 机器学习 机器学习
背景情况:
- 图像信号处理器 (ISP) 对图像质量至关重要.
- 现有的方法很难有效地产生多样化的图像风格.
- 控制ISP参数直接用于风格是具有挑战性的.
研究的目的:
- 引入一个插入式的图像信号处理器 (ISP),用于各种图像风格的增强.
- 开发一种方法来明确控制ISP的风格参数.
- 为了实现高效和可控的图像风格调整.
主要方法:
- 拟议的可控制图像信号处理器 (CRISP) 方法.
- 将高质量 (HQ) 图像风格的ISP参数编码为低维的隐藏代码.
- 在MIT-Adobe FiveK数据集上的实证评估.
主要成果:
- 克里斯普涵盖了广泛的图像风格,具有高效率.
- 克里斯普密切地估计了人类专家的参考风格.
- 用不同的图像风格获得更好的平均意见得分 (MOS).
- 与最先进的方法相比,CRISP的参数减少了2倍,FLOP减少了100倍.
- 优于PSNR和FLOP中的以前的工作,用于风格调整.
结论:
- 克里斯普提供高效和可控的图像风格增强.
- 该方法可显著降低计算成本和参数数量.
- 克里斯普可实现高质量的图像风格制作,并具有用户友好的控制.
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