摘要
小波变换具有优良的时频局部特性,但由于其尺度是按二进制变化的,存在“高频低分辨”这一缺陷.正交小波包分析能够将信号(图像)频带进行多层次划分,对多分辨分析没有细分的高频部分进一步分解,从而提高了频率分辨率,能有效地提取特定的频率成分.推导了小波包分析的基本原理,给出了基于正交小波包分析的遥感图像融合算法.最后,通过实例说明正交小波包分析的有效性和优越性.
Wavelet transform has excellent time-frequency local characteristics, anyhowits scale changes according to the binary system, thus it has defectsof high-frequency and low-resolution. Orthogonal wavelet packet transformcan divide signals(images) into multi-levels, and the high-frequency part which isn′t subdividedby the multi-resolution analysis continues to be decomposedfurther, and thus it improvesthe resolution of frequencyand can extractthe specific frequency componenteffectively. This paper deducesbasic principle of wavelet packet transform, and provides remote sensing images fusion algorithmbased on the orthogonal wavelet packet transform. At last,an instance provesthe validity and superiority of orthogonal wavelet packet transform.
出处
《海军工程大学学报》
CAS
北大核心
2005年第3期9-14,共6页
Journal of Naval University of Engineering
基金
国家自然科学基金资助项目(40401038)
江苏省高校自然科学基金资助项目(04KJD420193)
关键词
小波变换
正交小波包变换
图像融合
高频低分辨
wavelet transform
orthogonal wavelet packet transform
image fusion
high-frequency and low-resolution
