LabView Based Implementation of Image Denoising Algorithm using Wavelet Transform
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 2
Abstract
Digital image processing has become important in the areas of communication, medicine, remote-sensing, seismology, industrial automation, robotics, aerospace and education. Image denoising is the technique used to remove the noisy components from the image and also to preserve the information carrying components. Noise can be introduced in the image for various reasons as well as in different steps in image processing like image acquisition or image compression. Wavelet transform method using Neigh SURE (Stein’s Unbiased Risk Estimator) thresholding is applied for image denoising because of some distinct advantages offered by the technique like its quantization property. This method will be implemented on LabVIEW. In this method first wavelet transform decomposition is obtained over noisy image to get sub divided components then by thresholding the coefficient is adjust according to thresholding and filter out unwanted noise components. Then by applying inverse wavelet transform the denoised image is reconstructed called derived image. By means of PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) algorithm calculates the performance, quality and accuracy of the resultant image.
Authors and Affiliations
Lovika V. Bhagwatkar, Kalyani A. Akant, Milind M. Khanapurkar
Keywords
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- EP ID EP23194
- DOI http://doi.org/10.22214/ijraset.2017.2106
- Views 258
- Downloads 7
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