方向小波图像融合及多源图像性能评价

V. Shandilya, S. Ladhake
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引用次数: 0

摘要

图像融合是一种从多种输入图像中得到一幅复合输出图像的方法。我们可以融合失焦的图像,这里将不同焦距的图像作为输入,而期望输出图像清晰可见。今天有各种类型的传感器,具有各种各样的焦距,因此它们产生的图像中有些物体清晰,有些则不清晰。再一次,多传感器设备提供了大量的数据来分析和解释。所以我们需要某种机制将所有这些数据融合成一个数据。因此,对图像融合算法有一个基本的要求,即既能完成预期的任务,又能给出一些准确可靠的场景信息。在研究工作中,提出了一种将多幅图像进行融合,得到信息量更大、更可靠、更准确的单幅图像的方法。该方法是基于复小波变换与方向小波分解相结合的方法。该方法具有良好的方向选择性和良好的重建能力,这是图像融合的重要方面。最终融合的图像以这样一种方式增强,它对解释和分析很有用,并有助于提出有关场景的某些决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image fusion using direction wavelet approach and performance evaluation of multiple source images
Image fusion is the approach to get one composite output image from number of variety of input images. We can fuse images which are out of focus, here images of different focal length are considered as input whereas output image is expected to be clear and visible. There are various types of sensors available today having wide variety of focal length and hence they generate images in which some objects are clear some are not. Again multi-sensor devices provide huge data to analyze and interpret. So we require some sort of mechanism to fuse all this data into single one. Therefore there is a basic requirement of certain image fusion algorithm which will perform the desired task and gives some accurate and reliable information about the scene. In the research work a method is developed to perform the fusion of multiple images to get a single image which is more informative, reliable and accurate. The proposed method is based on complex wavelet transform with the combination of direction wavelet decomposition method. The method is good at direction selectivity, also perfect reconstruction which is very important aspect for fusion of images. The final fused image is enhanced in such a way that it is useful for interpretation and analysis and assists to come up with certain decision about the scene.
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