基于近似点扩展函数的X射线图像优化

基金项目:

省自然基金(60602041)

国家重点基金(60532080)

省自然基金(60772102)

详细信息

Optimization for X-Ray Image Based on Approximated Point Spread Function

摘要: 工业射线检测中, 由于射线成像系统、环境等因素的影响常引起图像质量的下降。通过对射线图像降质过程的分析, 针对探测器为线性移变系统的情况, 在反滤波信号恢复的基础上利用近似点扩展函数的算法对图像进行优化, 再用KNN算法对图像进行滤波。试验证明, 经该算法优化后的X射线图像效果优于同态滤波, 且该算法将反滤波近似为除法运算, 大大减少了运算时间, 有利于实时系统的应用。
- 图像优化 /
- 点扩展函数 /
- 反滤波
Abstract: In industrial X-ray testing, owing to the influence of X-ray imaging systems, the environment and other factors often cause the image degradation. By analyzing on image degradation process and aiming at the condition that the detector is linear shift variant system, using of the approximate point spread function algorithm to optimize the X-ray image was used on the basis of inverse filtering signal restoration, and then followed by the filtering for image by KNN algorithm. The experiment results showed that this method was superior to the homomorphic filter in detection effect of X-ray image optimized, and this method also approximately transformed inverse filtering algorithm into division algorithm and greatly reduced the computing time so it was in favor for the application of real-time system.
- Image optimization /
- Point spread function /
- Inverse filtering

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