Poisson Noise Reducing Bilateral Filter

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• 作者：Kirti V. Thakur ; ^{kirti79@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Omkar H. Damodare ; Ashok M. Sapkal
• 关键词：Poisson Noise ; Non-local mean filter ; Bilateral Filter.
• 刊名：Procedia Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：79
• 期：Complete
• 页码：861-865
• 全文大小：192 K

文摘

Noise removal is a classical problem but not yet solve completely. So researchers are attracted to this problem again and again. Poisson noise is signal dependent noise and to remove this kind of noise, additive noise removal techniques are not helpful. Existing state of art methods such as non-local mean filter, bilateral filter, BM3D algorithms works better for reducing additive noise. Non local mean filter and BM3D algorithms are further modified for Poisson noise reduction but they require more execution time to remove the noise. In this paper we proposed a spatial domain filter by modifying bilateral filter framework. Advantages of proposed filter are non-iterative nature, simplicity and edge preserving ability. It gives image quality comparable to current state of art method such as non-local mean filtering. Also, time required for this modified bilateral filter is very less than other techniques.