Poisson Noise Removal in Biomedical Imagesusing Non-Linear Techniques

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering

article

Jisha J U¹  Sureshkumar V¹ 

[1] Dept. of Electronics and Instrumentation, Valliammai Engineering college

关键词: Multi-Scale Variance Stabilizing Transform;    Fast Discrete Curvelet Transform;    Thresholding;    Null Hypothesis;    Signal to Noise Ratio;    Universal Image Quality Index.;   

来源: Research & Reviews

【 摘 要 】

Medical images have always been an important factor in diagnosis of disease. Poisson Noise in those images has always been a problem with the image clarity. We propose two technique which combines Multi-Scale Variance Stabilizing Transform (MS-VST), Fast Discrete Curvelet Transform (FDCT) with Thresholding and MS-VST, FDCT with Null Hypothesis testing for effectively removing the Poisson Noise from the medical images. The effectiveness of using these techniques has been analyzed using Peak Signal to Noise Ratio and Universal Image Quality Index.

【 授权许可】

Unknown