Compared with wavelet transform which is widely used in image processi ng,Tetrolet transform has a better directionality of the structure and can express texture f eatures of image precisely in dealing with high-dimensional signal.This paper introduces Tetrol et transform into different spectrum images for fusion to obtain a greater amount of informati on.F irstly,the Tetrolet transform was performed on the images which are fused to obtain high-p ass and low-pass subbands on different scales and in various directions.Then,a method based on local region gradient information was applied to low-pass subbands to get the low-pass fusi on coefficients, and a method based on neighboring region variance weighted-average was applied to high-pass subbands to get the high-pass fusion coefficients.Finally,the inverse Tetrole t transform was utilized to obtain fused image.Using a variety of images to perform fusion ex periment,all the results have shown that the fused image has more abundant features and more amou nt of information by using Tetrolet transform.The entropy and standard deviation of the fusion im age are better than those of the fused results by wavelet transform and PCA methods.The prop osed method can effectively improve target detection probability and reduce the false alarm rate of the ATR and visual identification systems.