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《Journal of Optoelectronics.Laser》 2013-11
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Adaptive image fusion based on image quality assessment parameter in FDST domain

CHEN Guang-qiu;GAO Yin-han;College of Instrumentation and Electrical Engineering,Jilin University;State Key Laboratory of Automobile Simulation and Control,Jilin University;  
To enhance multi-source images fusion accuracy,an adaptive fusion method based on image quality assessment parameters in finite discrete shearlet transform(FDST)domain is proposed.Source images are decomposed to subband images with multi-scale and multi-direction by FDST.The low-frequency subband fusion rule is based on structural similarity index with spatial frequency as coefficient weights and the fusion rule of regional window spatial frequency selection max is adopted in the high frequency subbands.Fused low and high frequency coefficients are reconstructed to image by finite discrete shearlet inverse transform.Corresponding fusion experiments are done by several sets of different modality images and objective performance assessments are conducted for fusion results.The experimental results indicate that the proposed algorithm performs better in subjective and objective assessments than a few existing multi-scale fusion techniques in the literature and can obtain better fusion performance.
【Fund】: 高等学校博士学科点专项科研基金(20110061110059);; 吉林省科技发展计划(20110326)资助项目
【CateGory Index】: TP391.41
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