Regarding this, a novel feature level approach to image fusion is proposed based on discrete dyadic wavelet transform for multi-scale image edge detection.
本文提出了一种基于离散二进小波变换的多尺度边缘检测和图像融合的方法，实现了特征级图像融合。
The properties of the wavelet transform and the discrete dyadic wavelet transform are discussed and a fast wavelet algorithm for one-dimensional signals is described.
论述了连续小波变换和离散小波变换的性质、方法，介绍了离散二进小波变换的快速算法。
To overcome pulse noise influence to image quality, discrete dyadic wavelet transform (DDWT) is used to reduce the noise influence and improve signal to noise ratio (SNR).
为了克服噪声对超声检测成像质量的影响，利用离散二进制小波变换的分解重构算法来降低脉冲噪声的干扰，提高超声图像的信噪比。
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