Many significant images contains some extent of noise, that is unexplained variation in data disturbances in image intensity which are either uninterpretable or out of interest. Image analysis is often simplified if this unwanted noise is filtered. For this image simplification, filtering in frequency domain is done. In this paper we will demonstrate the image sharpening by Gaussian & Butterworth high pass filter and jot some points revealing their differences.
The current literature documents a plethora of image denoising techniques in the fields of medical imaging, remote sensing, biometrics, surveillance and vegetation mapping. Therefore it is important to have brief insight into various types of noises in different type of images, for instance medical images, remote sensing images and natural images. This article encompasses the basic definition, history, usage and type of noise affecting some of the major types of imaging modalities. Besides this a brief discussion on the type of noise prevailing in remote sensing and natural images is also given. While designing an effective image denoising algorithm, one needs to be acquainted with the prior information about the noise prevalent in various types of images. Further, a brief idea about the basic principle, outlook, contrast levels and application of medical imaging modalities has also been presented in the context of this article.
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