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Image Fusion Based on Statistical Hypothesis Test Using Wavelet Transform
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 Title & Authors
Image Fusion Based on Statistical Hypothesis Test Using Wavelet Transform
Park, Min-Joon; Kwon, Min-Jun; Kim, Gi-Hun; Shim, Han-Seul; Lim, Dong-Hoon;
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Image fusion is the process of combining multiple images of the same scene into a single fused image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and military affairs. The widely used image fusion rules that use wavelet transform have been based on a simple comparison with the activity measures of local windows such as mean and standard deviation. In this case, information features from the original images are excluded in the fusion image and distorted fusion images are obtained for noisy images. In this paper, we propose the use of a nonparametric squared ranks test on the quality of variance for two samples in order to overcome the influence of the noise and guarantee the homogeneity of the fused image. We evaluate the method both quantitatively and qualitatively for image fusion as well as compare it to some existing fusion methods. Experimental results indicate that the proposed method is effective and provides satisfactory fusion results.
Image fusion;wavelet transform;hypothesis test;squared ranks test;
 Cited by
정상 웨이블렛 변환을 이용한 로버스트 영상 융합,김희훈;강승효;박재현;하현호;임진수;임동훈;

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