| 周飞,贾振红,杨杰,Nikola Kasabov.基于剪切波域改进Gamma校正的医学图像增强算法[J].光电子激光,2017,28(5):566~572 |
| 基于剪切波域改进Gamma校正的医学图像增强算法 |
| Medical image enhancement method based on improved Gamma correction in Shearlet domain |
| 投稿时间：2016-05-13 |
| DOI： |
| 中文关键词: 医学图像增强 剪切波变换 Gamma校正 自适应阈值 模糊对比度 |
| 英文关键词:medical image enhancement shearlet transformation Gamma correction adaptive t hreshold fuzzy contrast |
| 基金项目:教育部促进与美大地区科研合作与高层次人才培养(20142029)资助项目 (1.新疆大学 信息科学与工程学院,新疆 乌鲁木齐 830046； 2.上海交通大学 图像处理 与模式识别研究所,上海 200240； 3.新西兰奥克兰理工大学 知识工程与发现研究所,新西 兰奥克兰1020) |
|
| 摘要点击次数: 1051 |
| 全文下载次数: 0 |
| 中文摘要: |
| 为了解决医学图像在采集和传输过程中引入噪 声和干扰导致图像质量恶化从而严重影响医学诊断的问题,提出 一种基于剪切波(shearlet)域改进Gamma校正的图像增强方法。首先,通过剪切波变换,把 图像分解成高频 部分和低频部分；其次,用改进的Gamma校正处理剪切波分解后的低频部分以调整图像的整 体对比 度,采用改进的自适应阈值函数对高频部分进行去噪；最后,把剪切波反变换的重构图 像进行模糊对比 增强,以突出图像的细节信息。实验结果表明,本文算法的峰值信噪比(PSNR )、结构相似度(SSIM)和 绝对均值差(MAE)优于其他对比算法,尤其是PSNR的提升更加明显。这些 客观指标说明,本 文算法不仅能有效地抑制噪声,而且能明显改善增强对比度。从主观方面观察,本文算法与 其他算法相比,能获得更好的视觉效果。 |
| 英文摘要: |
| Noises and artifacts are introduced to medical images in the process of acquisit ion and transmission,which causes image degradation and further seriously affect s the clinical diagnoses.Therefore,in order to solve this problem,a medical imag es enhancement method based on shearlet transformation and improved gamma correctio n is proposed in this paper.First,the original image is decomposed into the shearlet domain with low-frequency component and high-frequency component.Then,the improved gamma correction is adopted for the low-frequency component to improve the global contrast of the image,and an adap tive threshold method is used for the removal of high-frequency image noise.Finally,the improved fu zzy contrast is used to enhance the details of the reconstruct image which is obtained by the sh earlet inverse transformation.The experimental results show that the proposed method is super ior to other comparative methods in peak signal to noise ratio (PSNR) ,structural similarity (SSIM) and mean absolute error (MAE),especially the PSNR is increased observably.These objective criterions indicate that the proposed method not only can remove image noise efficiently, but also significantly improve the contrast of image.In the subjective aspect, the proposed method can get better visual effect than other methods. |
| 查看全文 下载PDF阅读器 |
| 关闭 |
|
|
|
|
|