16-02-2013, 09:46 AM
Application of Image Fusion Using Wavelet Transform In Target Tracking System
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Abstract
The abstract The fusion of images is the process of combining two or more images into a single image retaining important features from each. Fusion is an important technique within many disparate fields such as remote sensing, robotics and medical applications. Wavelet based fusion techniques have been reasonably effective in combining perceptually important image features. Shift invariance of the wavelet transform is important in ensuring robust sub-band fusion. Therefore, the novel application of the shift invariant and directionally selective Dual Tree Complex Wavelet Transform (DT-CWT) to image fusion is now introduced. The successful fusion of images acquired from different modalities or instruments is of great importance in many applications, such as medical imaging, microscopic imaging, remote sensing, computer vision, and robotics. With 2D and 3-D imaging and image processing becoming widely used, there is a growing need for new 3-D image fusion algorithms capable of combining 2D & 3-D multimodality or multisource images.
Introduction
With the rapid advancements in technology, it is now possible to obtain information from multisource images. However, all the physical and geometrical information required for detailed assessment might not be available by analyzing the images separately. In multisensory images, there is often a trade-off between spatial and spectral resolutions resulting in information loss. Image fusion combines perfectly registered images from multiple sources to produce a high quality fused image with spatial and spectral information. It integrates complementary information from various modalities based on specific rules to give a better visual picture of a scenario, suitable for processing. An image can be represented either by its original spatial representation or in frequency domain. By Heisenberg’s uncertainty, information cannot be compact in both spatial and frequency domains simultaneously. It motivates the use of wavelet transform which provides a multiresolution solution based on time-scale analysis.
Multi-sensor image fusion system
Multi-sensor image fusion systems overcomes the
limitations of a single sensor vision system by
combining the images from these sensors to form a
composite image. Figure 1-1 shows an illustration of a
multi-sensor image fusion system. In this case, an
infrared camera is supplementing the digital camera
and their individual images are fused to obtain a fused
image. This approach overcomes the problems referred
to before, while the digital camera is appropriate for
daylight scenes, the infrared camera is suitable in
poorly illuminated ones.
Experimental results and discussion
Several image databases are built in order to test the system. A number of experiments are performed on different images as described below. We fuse the two images using different wavelet transform. The aim of the project is to test each technique by the calculation of execution time for 2D images and for some combinations for 3D images.
Conclusion
In this work a new approach to 3-D image fusion using wavelet transform. Several known 2-D WT fusion schemes have been extended to handle 3-D images have been proposed. The goal of this project is to present the new framework for 3-D image fusion using the wavelet transform, rather than to compare the results of the various fusion rules. Wavelet transform fusion diagrams have been introduced as a convenient tool to visually describe different image fusion schemes. A very important advantage of using 3-D WT image fusion over alternative image fusion algorithms is that it may be combined with other 3-D image processing algorithms working in the wavelet domain.