摘要
对比度、清晰度等视觉效果是影响图像质量的重要因素。针对光学遥感图像对比度和清晰度改善问题,提出了一种新的视觉效果自动增强模型。首先对输入图像的直方图采用非线性变换,在保持灰度级有效分布的前提下充分压缩灰度分布范围,从而获得优化的变换系数,然后再利用线性拉伸算法将图像灰度扩展至整个灰度域。实验和对比结果表明,所提出的增强模型在很小的信息熵损失条件下能较大幅度地提高图像的对比度和清晰度,获得比目前主要算法更好的增强结果且效果稳定,可适用于全色图像和彩色图像视觉效果的全自动化增强处理。
The image contrast and definition of remotely sensed image are the important factors of image quality. This paper presented a novel self-adaptive enhancement method for contrast and definition. Firstly,nonlinear transformation is operated on the histogram of an input image to reduce the distribution range of the image,and then linear stretch is used to expand the grey level to full permitted range. Experiments and comparison indicate that the presented method can improve the contrast and the definition with a little loss of information entropy and the enhanced results is rather fine than current main method of enhancement. Also,the presented method can be used to both panchromatic and colorful remotely sensed image.
出处
《西北大学学报（自然科学版）》
CAS
CSCD
北大核心
2016年第3期448-452,共5页
Journal of Northwest University（Natural Science Edition）
基金
国家自然科学基金资助项目(41171090)
关键词
直方图优化
对比度增强
清晰度增强
视觉效果改善
自适应增强
histogram optimization
contrast stretch
definition enhancement
vision effect improvement
self-adaptive enhancement
