Abstract: In order to solve the problem that the visual effect of enhanced image is poor and the detail is fuzzy, this paper proposes a new image enhancement algorithm. It calculates every pixel’s relative entropy between date model and uniform distribution model in the image, and sets a threshold to judge whether the pixel’s relative entropy is more than the threshold. If it is that, the pixel will be enhanced by the algorithm based on the neighborhood information of pixel, and other pixels will be enhanced by the algorithm of BHEPL. Experimental results show that the enhanced image by proposed algorithm has a good visual effect and its detail information is clearer.

Key words: relative entropy, image enhancement, neighborhood information, remote sensing image, visual effect, image detail

摘要： 针对图像增强后视觉效果较差和细节信息不明显的问题，提出一种新的图像增强算法。计算图像中各像素数据模型与均匀分布模型之间的相对熵，设定阈值，基于邻域信息对相对熵大于阈值的像素进行自适应对比度增强，其余像素采用平台限制的双直方图均衡算法进行增强。实验结果表明，与HE算法、BHEPL算法和PLIP_BHE算法相比，经过该算法增强后的图像具有更好的视觉效果和更明显的细节信息。

关键词: 相对熵, 图像增强, 邻域信息, 遥感图像, 视觉效果, 图像细节

CLC Number: 

• TN911.73