An Optimized Perona-malik Anisotropic Diffusion Function For Denoising Medical Image
Noise is the major problem in the field of image processing. In Medical image such as Ultrasound image, MRI data and Radar Images are affected by different types of noise. So it is the most important task to eliminate such noises. In image processing anisotropic diffusion is a technique for reducing image noise without removing significant parts of the image contents, such as edges, lines or other details that are important to represent the quality of the image. To acquire a better performance we state an another diffusion function that works efficiently to denoise an image without blurring the frontiers between different regions. To evaluate the performance we calculate the Signal to Noise Ratio, The Peak Signal to Noise Ratio, The Root Mean Square Error, The Edge Preservative Factor. This Function gives the better result with comparison to existing Perona-Malik anisotropic diffusion Function.
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Date
October 2017 -
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902.3KB -
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