计算机科学 ›› 2009, Vol. 36 ›› Issue (9): 287-289.
• 图形图像及体系结构 • 上一篇 下一篇
葛雯,高立群
出版日期:
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基金资助:
GE Wen,GAO Li-qun
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摘要: 针对传统可分离小波图像融合过程中存在部分边缘丢失和纹理信息模糊的问题,提出了突出图像细节和消减图像模糊性的融合算法。该算法在非分离小波分解框架下,对反映图像近似内容的低频分量采用局部模糊嫡极大值融合规则,对反映图像细节特征的高频分量提出了区域亮度细节占优加权的融合规则。最后通过非分离小波逆变换重构融合图像。实验结果表明,该算法能在保留源图像信息的情况下,提高融合图像的清晰度,增强细节信息及亮度对比度。
关键词: 可分离小波变换,非分离小波变换,模糊嫡,亮度对比度,图像融合
Abstract: In the view of this situation that in the image fusion process of the traditional separable wavelet transform,there arc problems of lost part edges and blurred texture information, a fusion algorithm that highlights image details and reduces the image blurring was proposed. Under the non-separable wavelet decomposed frame,a fusion rule of local blurred entropy maximum was used for the low-frequency component which reflects approximate content, and a fusion rule of region brightness details priority weighted was used for the high-frequency component which reflects features and details of image. Finally, the fusion image was reconstructed through an inverse transform of non-separable wavelet.Experimental results show that under the condition of reservation of source image information, this algorithm improves the clarity of fused image, enhances details information and brightness contrast.
Key words: Separable wavelet transform, Non-separable wavelet transform, Fuzzy entropy, Brightness contrast, Image fusion
葛雯,高立群. 基于模糊熵和非分离小波变换的图像融合算法[J]. 计算机科学, 2009, 36(9): 287-289. https://doi.org/
GE Wen,GAO Li-qun. Image Fusion Algorithm Based on Fuzzy Entropy and Non-separable Wavelet Transform[J]. Computer Science, 2009, 36(9): 287-289. https://doi.org/
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