Color image enhancement of low-resolution images captured in extreme lighting conditions

摘要

Security and surveillance videos, due to usage in open environments, are likely subjected to low resolution, underexposed, and overexposed conditions that reduce the amount of useful details available in the collected images. We propose an approach to improve the image quality of low resolution images captured in extreme lighting conditions to obtain useful details for various security applications. This technique is composed of a combination of a nonlinear intensity enhancement process and a single image super resolution process that will provide higher resolution and better visibility. The nonlinear intensity enhancement process consists of dynamic range compression, contrast enhancement, and color restoration processes. The dynamic range compression is performed by a locally tuned inverse sine nonlinear function to provide various nonlinear curves based on neighborhood information. A contrast enhancement technique is used to obtain sufficient contrast and a nonlinear color restoration process is used to restore color from the enhanced intensity image. The single image super resolution process is performed in the phase space, and consists of defining neighborhood characteristics of each pixel to estimate the interpolated pixels in the high resolution image. The combination of these approaches shows promising experimental results that indicate an improvement in visibility and an increase in usable details. In addition, the process is demonstrated to improve tracking applications. A quantitative evaluation is performed to show an increase in image features from Harris corner detection and improved statistics of visual representation. A quantitative evaluation is also performed on Kalman tracking results.