摘要
针对传统的小波系数线性增强方法处理图像时容易导致过增强的问题,提出基于自适应阈值的增强方法。首先对图像进行二维小波分解,然后针对低频系数的统计信息得出最优的自适应阈值,根据阈值对低频系数进行处理,最后小波重构得到增强图像。实验结果表明这种方法对低对比度图像有较好的增强效果,该方法适合于图像的增强处理。
Traditional linear enhancement method based on wavelet often causes over-enhancement problem for images. But enhancement algorithm based on adaptive threshold can avoid that problem. In this algorithm, an image is first decomposed to get wavelet coefficients. Then, optimal threshold is obtained according to statistical information of low frequency wavelet coefficients. Then low frequency coefficients are processed according to the threshold. Finally, wavelet reconstruction is operated to obtain enhanced image. The experiments show that this algorithm has excellent enhancement effect for low- contrast images.
出处
《信息技术》
2015年第9期36-39,共4页
Information Technology
基金
国家自然科学基金项目(61371142)
2013北京市教委专项(PXM2013_014212_000026)
关键词
小波变换
增强
图像增强
自适应阈值
低对比度图像
wavelet transform
enhancement
image enhancement
adaptive threshold
low-contrast image