红外图像全局和局部对比度增强的非线性增益法

Non-Linear Gain Algorithm to Enhance Global and Local Contrast for Infrared Image

提出一种基于模拟退火算法和离散平稳小波变换增强红外图像全局和局部对比度的非线性增益算法·基于原始红外图像的灰度直方图提出一种判据,利用该判据判断原始红外图像的对比度类型,以指导模拟退火算法的搜索方向和初值的选取;并利用模拟退火算法优化非线性灰度变换参数,实现对图像进行全局对比度增强·对全局增强后的图像进行离散平稳小波变换,分别对各个分解层的高频子带利用所提出的非线性增强算法进行细节增强·实验结果表明,该算法在有效地提高红外图像整体对比度的同时,能突出红外图像中目标的细节部分信息,在视觉质量上优于传统的直方图均衡法、反锐化掩膜法等·

A non-linear gain algorithm for both global and local contrast enhancement of infrared images is proposed, and it is based mainly on the simulated annealing and discrete stationary wavelet transform. Firstly, a histogram-based criterion is introduced, and by which the type of the original image is determined, then followed by the selection of searching direction as well as the initial values of simulated annealing. Secondly, the global contrast enhancement is obtained by optimizing the non-linear gray transform parameters by the simulated annealing. Thirdly, the globally enhanced image is further transformed by the discrete stationary wavelet transform to enhance the local details by a non-linear operator in the high frequency subbands of each decomposition level. The experiments show that the proposed algorithm can both enhance the global contrast of the image and the details of the target within the image. It performs better than the traditional histogram equalization method and the un-sharp mask method in terms of visual quality.