Enhancing the Detectability of Subtle Changes in Multispectral Imagery Through Real-time Change Magnification.

摘要

In this project we adapted the newly developed Phase-Based Video Processing (PBVP) algorithm to enhance the visibility of subtle temporal changes (movement or temperature fluctuations) in multiband (visual, near-, shortwave- and longwave-infrared) imagery while simultaneously reducing dynamic noise. We successfully applied the adapted algorithm to enhance the visibility of small movements in the Visual, Near-Infrared and Thermal (LWIR) bands of multiband video sequences registered by the TNO TRI-band Color Low-light OBServation System (TRICLOBS), and in dynamic short-wave infrared (SWIR) sequences provided by AFRL/711HPW/RHCV. In addition, we applied the method for the early detection of change processes, for the estimation of a person s heart rate from facial videos, and to enhance the visibility of landmines in polarized SWIR sequences. In the course of the project we also developed a simple Power-Logarithm (Pow-Log) histogram modification operator to enhance image contrast, and a new color-to-gray conversion algorithm that retains both the overall appearance and the discriminability of a three channel color image when represented as a single band (grayscale) image.