J4 ›› 2015, Vol. 32 ›› Issue (5): 550-554.

• 图像与信息处理 • 上一篇    下一篇

基于多尺度灰度变换的图像增强研究

廖斌,刘鸳鸳   

  1. 湖北大学计算机与信息工程学院,湖北 武汉430062
  • 收稿日期:2014-09-01 修回日期:2014-10-22 出版日期:2015-09-28 发布日期:2015-09-28
  • 通讯作者: 廖斌(1979-),湖北人,副教授,博士,从事计算机图像视频处理的研究 E-mail:goldgoat@126.com
  • 基金资助:

    国家自然科学基金资助(61300125)

Research on image enhancement using multi-scale gray-level transformation

Liao Bin, Liu Yuanyuan   

  1. School of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China
  • Received:2014-09-01 Revised:2014-10-22 Published:2015-09-28 Online:2015-09-28

摘要:

为了提高图像增强效果,有效地保持原始图像细节,提出了一种基于多尺度灰度变换的图像增强方法。利用梯度域递归双边滤波对原始图像进行多尺度分解。基于小波变换,将分解层的子带分别作灰度变换。根据变换后的各个子带重构得到分解层的增强结果,并在其基础上实现图像的整体增强。对比直方图均衡化、灰度变换,提出的方法增强效果更好,并且保图像细节。利用客观性能指标对增强结果进行评价。实验结果表明,提出的方法有效,并具有结构简单,计算复杂度低的特点。

关键词: 图像处理, 图像增强, 多尺度灰度变换, 梯度域, 递归双边滤波

Abstract:

In order to improve the performance of image enhancement, effectively preserve original image details, an image enhancement method using multi-scale gray-level transformation was presented. The original image was decomposed into multi-scale layers using gradient domain based recursive bilateral filtering. Based on wavelet transform, the subcinctures of decomposed layers were transformed respectively in the gray-level. The overall image enhancement was realized based on the enhancement results of decomposed layers, which were reconstituted with the transformed subcinctures. Compared with histogram equalization and gray-level transformation, the proposed method performed better in image enhancement, and preserved details. The performance of the enhancement results was evaluated by the objective indicator. The experimental results show that the proposed method has excellent effect, simple structure and lower computational complexity.

Key words: image processing, image enhancement, multi-scale gray-level transformation, gradient domain, recursive bilateral filtering