AN IMAGE FUSION USING WAVELET AND CURVELET TRANSFORMS

Abstract

This Image fusion is a data fusion technology which keeps images as main research contents. It refers to the
techniques that integrate multi-images of the same scene from multiple image sensor data or integrate multi images of the
same scene at different times from one image sensor. The image fusion algorithm based on Wavelet Transform which faster
developed was a multi-resolution analysis image fusion method in recent decade. Wavelet Transform has good time-frequency
characteristics. It was applied successfully in image processing field. Nevertheless, its excellent characteristic in onedimension can’t be extended to two dimensions or multi-dimension simply. Separable wavelet which was spanning by onedimensional wavelet has limited directivity. This paper introduces the Curvelet Transform and uses it to fuse images. The
experiments show that the method could extract useful information from source images to fused images so that clear images
are obtained. In this paper we put forward an image fusion algorithm based on Wavelet Transform and the Curvelet
Transform. Low and high frequency coefficients are choosen according to different frequency domain after Wavelet and the
Curvelet Transform. In choosing the low-frequency coefficients, the concept of local area variance was chosen to measuring
criteria. In choosing the high frequency coefficients, the window property and local characteristics of pixels were analyzed.
Finally, the proposed algorithm in this article was applied to experiments of multi-focus image fusion and complementary
image fusion.