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Qualitative and Quantitative Evaluation of Image Denoising Techniques
Author(s) -
Charandeep Singh Bedi,
Himani Goyal
Publication year - 2010
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/1313-1775
Subject(s) - computer science , image denoising , artificial intelligence , noise reduction , image (mathematics) , computer vision , pattern recognition (psychology) , data science , information retrieval
Digital Imaging plays important role in major areas of life such as clinical diagnosis etc. But it faces problem of speckle noise. Speckle noise is referred as texture‘ in medical literature and it may contain useful diagnostic information. Speckle has a negative impact on ultrasound images, as the texture does not reflect the local echogenicity of the underlying scatterers. Physicians generally prefer original noisy images, more willingly than the smoothed versions, even if they are more sophisticated, can destroy some relevant image details. Thus, it is essential to develop noise filters, which can preserve the features that are of interest to the physician. One of the most prevalent cases is distortion due to additive white Gaussian noise, which can be caused by poor image acquisition or by transferring of the image data in noisy communication channels. Moreover there is a long list of image denoising techniques. But problem is that which technique is to be used and for what kind of format. In this paper, we have discussed various spatial filters in chapter 1. The comparison of the results gives the conclusion and the future scope of the discussion.

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