MULTI-SPECTRAL IMAGE FUSION METHOD BASED ON WAVELET TRANSFORMATION

The paper focuses on image fusion between multi-spectral images and panchromatic images using a wavelet analysis method with good signal processing and image processing traits. A new weighting technique is developed based on wavelet transformation for the fusion of a high spatial resolution image and a low-resolution, multi-spectral image. The method improves a standard wavelet merger for merging the lower frequency components of a multi-spectral image and its high spatial resolution image by means of local deviation rules with weighting average. And then the merged image is reconstructed by an inverse wavelet transform using the fused approximation and details from the high spatial resolution image. Also, a multi-spectral images fusion algorithm is proposed based on wavelet transform characteristic of human vision system. Firstly, perform a wavelet multi-scale transformation of each source image. Then a new fusion regular is presented based on human vision system corresponding high (low) frequency components are divided into several blocks, and contrast error of every block is calculated, an adaptive threshold selection is proposed to decide which should be used to construct the new high (low) frequency components. Finally, the fused image is obtained by taking inverse wavelet transform. The experimental results show that the new method presented is clearly better in not only preserving spectral and improving spatial presentation, but also avoiding mosaic occurring