计算机科学 ›› 2015, Vol. 42 ›› Issue (5): 320-323.doi: 10.11896/j.issn.1002-137X.2015.05.065
• 图形图像与模式识别 • 上一篇
高继森,董亚楠,沈 瑜,张春兰
GAO Ji-sen, DONG Ya-nan, SHEN Yu and ZHANG Chun-lan
摘要： 针对红外图像目标物体能量高以及可见光图像细节信息丰富的特点,提出一种基于改进的Tetrolet变换的红外与可见光图像融合算法。对红外和可见光图像进行多尺度、多方向分解,在低频融合规则上,对区域能量进行适当缩放,突出红外目标,保留可见光背景信息。实验结果表明,对Tetrolet变换模板的选择的改进,有助于获取更多高频信息；融合算法相对于传统的算法不仅增强了图像对比度,改善了主观视觉效果,而且在客观标准上有了一定提高。
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