基于第二代小波变换的图像融合方法及性能评价

提出了一种基于小波提升方案的图像融合新算法. 与传统基于卷积的小波变换融合方法相比, 新算法具有计算简单、融合速度快、所需内存少以及有利于算法的在线快速实现等优点. 此外, 还提出了一种基于区域特征选择的新的融合策略, 针对不同类型的多源图像进行了融合仿真实验, 并采用主观视觉判断与客观评价准则相结合的方式, 对不同变换方式、不同融合规则以及不同分解层数对融合效果的影响进行了比较分析. 实验结果表明本文提出的融合算法和融合策略具有优越的融合性能, 并取得了令人满意的融合效果.

An Image Fusion Algorithm Based on Second Generation Wavelet Transform and Its Performance Evaluation

A novel image fusion algorithm based on wavelet lifting scheme is presented.The lifting scheme is a new idea of constructing wavelets and has several unique advantages over conventional convolution-based wavelet transform.It allows for an in-place implementation of wavelet transform and reduces computation time and memory requirement greatly.So in this fusion algorithm,the lifting wavelet transform is employed to decompose and reconstruct images to realize fast image fusion.Meanwhile,a new local feature-based fusion rule is put forward to improve fusion quality and extract all significant features from multi-source images.Extensive experiments on the fusion of registered SPOT Panchromatic/multi-spectral images,multi-focus digital camera images,and medical MRI/PET images have been performed.Finally,visual judgment and several objective evaluation criterions are taken as the means of assessing fusion performance.The experimental results show that the new approach is very effective and is able to fuse multi-source images.