基于反向直方图的红外序列测量图像灰度变换方法

An Image Gray Scale Transformation Method Based on Inverse Histogram for Infrared Sequence Measurement Image

由于红外测量传感器具有感应范围宽,有效信息范围窄的特点,导致常规灰度变换方法损失目标有效信息,转换后的图像对比度低,图像质量较差。针对此问题,采用反向直方图理论,根据红外测量图像的灰度分布特性及处理要求,提出了一种利用反向直方图理论,进行红外序列测量图像灰度变换的方法。根据目标灰度变化趋势,扩展了目标灰度范围,压缩了背景及噪声的灰度级别,取得了良好的视觉效果。实验结果表明,该方法能够在增强目标图像细节的同时,完整的保留了图像背景信息,图像不失真。

The infrared measurement sensor has the characteristics of wide sensing range and narrow effective information scope, resulting in the problems that the conventional gray-scale transformation method may lose effective target information, the low image contrast ratio and poor image quality. According to these problems, an infrared sequence measurement image gray scale transformation method using inverse histogram theory based on gray scale distribution characteristics and processing requirements is proposed. According to the trend of target gray scale, the gray scale scope of the target is expanded, the gray level of the background and the noise is compressed, and the better visual effect is achieved. Experimental results show that the method can preserve complete image background information and the images without distortion, while enhancing the details of the target image.