| 基于提升格形态小波的生物芯片图像增强 |
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| 引用本文： | 胡翔宇,唐小萍.基于提升格形态小波的生物芯片图像增强[J].光电工程,2007,34(12):82-86. |
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| 作者姓名： | 胡翔宇 唐小萍 |
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| 作者单位： | 1. 中国科学院光电技术研究所,四川,成都,610209;中国科学院研究生院,北京,100039
2. 中国科学院光电技术研究所,四川,成都,610209 |
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| 基金项目： | 国家自然科学基金
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中国科学院西部之光人才计划 |
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| 摘 要： | 提出一种使用提升格形态小波进行生物芯片图像滤波增强的方法。根据生物芯片图像的样点和噪声区域的大小选择合适的结构元素或者预测-升级算子，并通过形态学算子或者提升格构造形态小波分解和重构形式。利用形态小波的不同级连方式和高频系数的处理实现生物芯片图像的滤波增强。实验表明，该方法可以有效地结合形态学和小波滤波的优势，降低了运算量，取得良好的生物芯片图像增强效果。
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| 关 键 词： | 生物芯片 图像增强 提升格 形态小波 |
| 文章编号： | 1003-501X(2007)12-0082-05 |
| 收稿时间： | 2007/5/13 |
Biochip image enhancement based on morphological lifting scheme wavelet |
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| HU Xiang-yu,TANG Xiao-ping.Biochip image enhancement based on morphological lifting scheme wavelet[J].Opto-Electronic Engineering,2007,34(12):82-86. |
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| Authors: | HU Xiang-yu TANG Xiao-ping |
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| Abstract: | A new approach for filtering and enhancing biochip image was proposed based on morphological lifting wavelet. Proper structural element or predict-update operator was selected according to sizes of signal spots and noises. Morphological wavelet transform were constructed by morphological operator or lifting scheme. Different sequential morphological wavelet transform and processing for high-frequency coefficient were used to enhance biochip images. The approach was tested in a variety of biochip images, and better antinoise and efficient performances were realized. The results demonstrate that it integrates the advantages of wavelet and morphology approach in effect. |
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| Keywords: | biochip image enhancement lifting scheme morphological wavelet |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
