【摘要】 红外成像技术具有隐蔽性强、环境适应能力强、可探测隐蔽物体的优点,因此被广泛应用于军事等领域。受成像原理、硬件设备及环境等因素影响,导致的红外图像整体对比度低、细节模糊、噪声多、视觉效果差等特性,限制了红外图像应用范围。本文利用红外图像自相关性与可见光图像自相关性判断红外图像与可见光图像相关性;并利用红外图像与可见光图像相关性增强红外图像细节信息。实验结果表明,基于异源图像引导的红外图像增强算法,在增强图像对比度、图像细节,改善图像视觉效果的基础上,可有效增强图像细节清晰度。更多还原

【Abstract】 Infrared imaging technology has several obvious advantages such as strong concealment,environmental adaptability,hidden objects detecting. Because of these advantages,Infrared imaging technology has been widely applied in military,aerospace,industrial testing,medical diagnosis and other fields.Affected by the image-forming principle,hardware equipment,environmental and other factors,Infrared image has the characteristics of low contrast,blurred image details,noise-corrupted,poor visual effect and so on. We proposed an infrared image enhancement algorithm based on heterogeneous image correction. We use the heterogeneous( visible) image to guide the infrared image detail enhancement:First,we propose to use the infrared image autocorrelation and the visible image autocorrelation to judge the similarity between the infrared image and the visible image. Secondly,we propose to use the infrared image and the visible image correlation similarity enhancement infrared image detail information. The experiment results demonstrate that our algorithm based on heterogeneous image correction can effectively enhance the image detail clearly.更多还原