针对含有低亮度低对比度区域的图像,提出基于局部自适应拉升窗(LASW)的复合图像增强算法。通过研究目前一系列基于局部操作的空域图像增强算法,提出全局和局部操作结合的总体思路;首先使用高提升拉普拉斯(Laplacian)反锐化掩模(UM)增强以获得较多的隐藏细节和边缘信息,然后构造局部自适应拉升窗大幅增强低对比度图像细节,同时使用自适应滤波器进行掩模平滑操作；最后根据局部增强结果进行全局修正。仿真实验表明,在绝对误差、图像熵等评价指标下,该算法使低对比度图像尤其当含有低亮度微弱局部信息时,获得了较好的增强效果。

Images suffering from poor luminance and contrast need enhancement before further processing or analysis. An algorithm based on local adaptive stretching window (LASW) technique is proposed. Since spatial contrast enhancement techniques by local manipulations show the pros and cons,the method combined with local and global manipulations is much more reasonable. Firstly,the high boost Laplacian unsharp mask (UM) operator is conducted for more hiding and edged information,then the LASW is operated on low contrast regions to develop details,and a locally adaptive filter is used to smooth the image further. At last,the global contrast adjustment is made after local manipulations. Experimental results show the good performance of the proposed algorithm with measure rules of enhancement by absolute mean brightness error and entropy,especially in the case of weak and low-contrast information in the image.