Conference Paper

An illuminance-reflectance nonlinear video enhancement model for homeland security applications

Dept. of Electr. & Comput. Eng., Old Dominion Univ., Norfolk, VA
DOI: 10.1109/AIPR.2005.14 Conference: Applied Imagery and Pattern Recognition Workshop, 2005. Proceedings. 34th
Source: DBLP

ABSTRACT A illuminance-reflectance model based video stream enhancement algorithm is proposed for improving the visual quality of digital video streams captured by surveillance camera under insufficient and/or nonuniform lighting conditions. The paper presents computational methods for estimation of scene illuminance and reflectance, adaptive dynamic range compression of illuminance, and adaptive enhancement for mid-tone frequency components. The images are processed in a similar way as human eyes sensing a scene. The algorithm demonstrates high quality of enhanced images, robust performance and fast processing speed. Compared with Retinex and multi-scale retinex with color restoration (MSRCR), the proposed method shows a better balance between luminance enhancement and contrast enhancement as well as a more consistent and reliable color rendition without introducing incorrect colors. This is an effective technique for image enhancement with simple computational procedures, which makes real-time enhancement for homeland security application successfully realized. The application of this image enhancement technique to the FRGC images yields improved face recognition results

0 Bookmarks
 · 
168 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured in the high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm which provides dynamic range compression preserving the local contrast and tonal rendition is a very good candidate in aerial imagery applications such as image interpretation for defense and security tasks. This algorithm can further be applied to video streaming for aviation safety. In this paper the latest version of the proposed algorithm which is able to enhance aerial images so that the enhanced images are better then direct human observation, is presented. The results obtained by applying the algorithm to numerous aerial images show strong robustness and high image quality.
    Recent Advances in Space Technologies, 2009. RAST '09. 4th International Conference on; 07/2009
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.
    Visual Information Processing XVIII, 14 April 2009, Orlando, Florida, USA; 01/2009
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: An adaptive technique for image enhancement based on a specifically designed nonlinear function is presented in this paper. The enhancement technique constitutes three main processes-adaptive intensity enhancement, contrast adjustment, and color restoration. A sine function with an image dependent parameter is used to tune the intensity of each pixel in the luminance image. This process provides dynamic range compression by boosting the luminance of darker pixels while reducing the intensity of brighter pixels and maintaining local contrast. The normalized reflectance image is added to the enhanced image to preserve the details. The quality of the enhanced image is improved by applying a local contrast enhancement followed by a contrast stretch process. A basic linear color restoration process based on the chromatic information of the original image is employed to convert the enhanced intensity image back to a color image. The performance of the algorithm is compared with other state of the art enhancement techniques and evaluated using a statistical image quality evaluation method.
    Visual Information Processing XVII, 18 March 2008, Orlando, Florida, USA; 01/2008

Full-text

View
6 Downloads
Available from