多方向多尺度变换能以更稀疏的方式表示图像的边缘和纹理等几何特征，有利于图像压缩。
The proposed transform could represent the geometrical features such as edges and texture more sparsely, which is of great benefit to image compression.
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。
Regarding this, a novel feature level approach to image fusion is proposed based on discrete dyadic wavelet transform for multi-scale image edge detection.
图象多尺度边缘是图象的重要特征，已广泛应用于图象处理和计算机视觉等多个领域。
Image multiscale edges are important features for image representation. It has been used in image processing and computer vision.
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