Reconfigurable Processor for Energy-Scalable Computational Photography

📋 论文概要

本文提出了一种面向能量可扩展计算摄影的可重构处理器，通过硬件加速实现高计算复杂度的非线性滤波（如双边滤波），解决了实时处理的计算需求。该处理器支持多种计算摄影应用，如高动态范围成像和低光增强。

💡 主要创新点

• 提出了一种可重构处理器架构，能够针对计算摄影中的非线性滤波算法进行能量-性能权衡的硬件配置。
• 实现了能量可扩展性，允许根据应用需求动态调整计算精度和功耗，适用于移动设备。

🏷 关键词

📄 原文摘要

photography [1], enable capture and synthesis of images that could not be captured with a traditional camera. Non-linear filtering techniques like bilateral filtering [2] form a significant part of computational photography. These techniques have a wide range of applications, including High-Dynamic Range (HDR) imaging [3], Low-Light Enhanced (LLE) imaging [4], tone management and video enhancement. The high computational complexity of such multimedia processing applications necessitates fast hardware implementations [5] to enable real-time processing. This paper describes a hardware implementation of a reconfigurable multi-application processor for computational photography. A software-based bilateral grid structure is described in [6], which enables fast

👥 作者与机构

Rahul Rithe1, Priyanka Raina1, Nathan Ickes1, Srikanth V. Tenneti2, Anantha P. Chandrakasan1

Massachusetts Institute of Technology, Cambridge, MA, California Institute of Technology, Pasadena, CA 1 2 Computational photography applications, such as lightfield