应用参数化对数模型增强图像细节及对比度

传统红外图像增强方法由于未考虑人眼视觉特性而存在"超区间值"，故极易丢失图像细节。本文结合对数图像处理（LIP）理论，提出了基于参数化对数模型（PLIP）的平台直方图均衡图像增强方法。该方法首先将图像变换为灰度色调函数；然后应用PLIP模型对变换后的图像进行重建，结合平台直方图均衡化来增强图像的对比度和细节信息，并利用图像评价函数（EMEE）与信息熵（En）确定模型的参数值。最后，研制了算法硬件平台，分别用中波和长波红外成像系统对算法进行了实验验证。实验结果显示：该方法对不同场景的图像均可取得很好的增强效果，图像的EMEE值比传统的平台直方图均衡算法提高至少5倍以上，对改善图像质量和视觉效果具有实用价值。

Enhancement of image detail and contrast by parameterized logarithmic framework

The traditional infrared image enhancing has "over range value" caused by not taking vision characters of human eye into consideration, therefore, image details are lost. In this paper, an enhanced algorithm based on Parameterized Logarithmic Image Pocessing(PLIP) model was proposed for histogram equalization image processing. First, the image was converted to a gray tone function. Then, the image was reconstructed by the PLIP model and its contrast and details were enhanced by combined plateau histogram equalization. The model parameters were determined by evaluation of function (Measurement of Enhancement by Entropy,EMEE) and information entropy (En). Finally, the hardware platform of the algorithm was developed, and the algorithm was verified respectively by the medium-wave and long-wave infrared image systems. Experimental results show that the method can obtain better enhanced effect for different images. The EMEE of the enhanced image is more than 5 times than traditional plateau histogram equalization algorithm. The results show that this method has an application value to improve the image quality and visual effect.