30-05-2012, 11:37 AM
Image-based fusion for video enhancement of night-time surveillance
[attachment=23469]
Introduction
Video surveillance is often more important in the dark environment
since many activities of interest often occur in the
dark environment.1, 2 Video enhancement plays a key part
in night-time video surveillance so that the objects or activities
of interest can be clearly monitored. The problem
of video enhancement for low quality video has become
increasing by acute.3 The goal of the enhancement4 is to
improve the visual appearance of the video, or to provide a
“better” representation for further processing, such as analysis,
detection, segmentation, and recognition. However, it is
still a challenging problem for night-time video applications.
To traditional algorithms, when the background is enhanced,
the contrast often remains low, or the noise is often greatly
enhanced.
The Proposed Algorithms
The detailed procedures of the proposed method can be described
as in Fig. 1. It should be noted that in Fig. 1, the
‘day-time image’ as well as the ‘night-time image’ are the
high-quality images for providing a better enhanced background
and the night-time video is the actually low-quality
input that we need to enhance. In the following, we will
describe algorithm.
Enhanced (Night-time) Video
Due to the low contrast, we can not clearly extract moving
objects from the dark background. We propose an
enhanced-video step to facilitate the extraction moving
objects. The tone-mapping approach is used to enhance
the video frames and to separate an image into details
and large scale features. More specifically, the nonlinear
tone mapping function is used to attenuate image details
and to adjust the contrast of large scale features,12 as in
Eqn. (6).
Final Experimental Results and Conclusions
In this paper, we propose a novel algorithm to enhance nighttime
video. We focus on addressing the following two key
issues for video enhancement. (1) illumination-based fusion
for enhancement background image. (2) Moving objects of
region fusion for improving sharpness of the moving objects.
Figures 2 and 3 show the experimental results.
[attachment=23469]
Introduction
Video surveillance is often more important in the dark environment
since many activities of interest often occur in the
dark environment.1, 2 Video enhancement plays a key part
in night-time video surveillance so that the objects or activities
of interest can be clearly monitored. The problem
of video enhancement for low quality video has become
increasing by acute.3 The goal of the enhancement4 is to
improve the visual appearance of the video, or to provide a
“better” representation for further processing, such as analysis,
detection, segmentation, and recognition. However, it is
still a challenging problem for night-time video applications.
To traditional algorithms, when the background is enhanced,
the contrast often remains low, or the noise is often greatly
enhanced.
The Proposed Algorithms
The detailed procedures of the proposed method can be described
as in Fig. 1. It should be noted that in Fig. 1, the
‘day-time image’ as well as the ‘night-time image’ are the
high-quality images for providing a better enhanced background
and the night-time video is the actually low-quality
input that we need to enhance. In the following, we will
describe algorithm.
Enhanced (Night-time) Video
Due to the low contrast, we can not clearly extract moving
objects from the dark background. We propose an
enhanced-video step to facilitate the extraction moving
objects. The tone-mapping approach is used to enhance
the video frames and to separate an image into details
and large scale features. More specifically, the nonlinear
tone mapping function is used to attenuate image details
and to adjust the contrast of large scale features,12 as in
Eqn. (6).
Final Experimental Results and Conclusions
In this paper, we propose a novel algorithm to enhance nighttime
video. We focus on addressing the following two key
issues for video enhancement. (1) illumination-based fusion
for enhancement background image. (2) Moving objects of
region fusion for improving sharpness of the moving objects.
Figures 2 and 3 show the experimental results.