A MULTI-SENSOR IMAGE FUSION ALGORITHM BASED ON MULTI-SCALE FEATURE ANALYSIS

The multi-sensor image fusion technology can obtain a more accurate and reliable image to understand the scene or recognize the target more easily. However, most existing algorithms are mainly based on optical images, which are highly susceptible by media interference, and cannot save the textural feature and color information at the same time. In view of these problems, this paper presents a multi-sensor image fusion algorithm based on multi-scale feature analysis. After preprocessing, the SAR image is divided into irregular area and regular area based on an adaptive segmentation method. Then, these two areas are separately decomposed using SIDWT algorithm to extract image texture. A multi-scale feature analysis rule is proposed to be used on wavelet coefficients of SAR and PAN image. The fused image is finally got after inverse wavelet transform with new wavelet coefficients. Experimental results showed the effectiveness of the proposed algorithm by subjective and objective evaluation.