Data Processing Through Image Processing using Gaussian Minimum Shift Keying

Abstract

Image Denoising is an important pre-processing task which is used before further processing of image. The purpose of denoising is to remove the noise while retaining the edges and other detailed features. This noise gets introduced during the process of acquisition, transmission and reception and storage and retrieval of the data. Due to this there is degradation in visual quality of image. Wavelets play a major role in image compression and image denoising as they support the property of sparsity and multi resolution structure. Wavelet Thresholding is important technique in wavelet domain filtering. Many image filters are found which perform well when the noise conditions are low. But as the noise conditions go on increasing their performance gets degraded. Thus, it is felt that there is sufficient scope to investigate and develop quite efficient but simple algorithms to suppress moderate and high power noise in images. Nadiya Mehraj | Harveen Kour "Data Processing Through Image Processing using Gaussian Minimum Shift Keying" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18819.pdf

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  • EP ID EP410983
  • DOI -
  • Views 59
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How To Cite

(2018). Data Processing Through Image Processing using Gaussian Minimum Shift Keying. International Journal of Trend in Scientific Research and Development, 2(6), 977-981. https://europub.co.uk/articles/-A-410983