Abstract
The VisuShrink is one of the important image denoising methods. It however does not provide good quality of image due to removing too many coefficients especially using soft-thresholding technique. This paper proposes a new image denoising scheme using wavelet transformation. In this paper, we modify the coefficients using soft-thresholding method to enhance the visual quality of noisy image. The experimental results show that our proposed scheme has better performance than the VisuShrink in terms of peak signal-to-noise ratio (PSNR) i.e., visual quality of the image.
Highlights
One of the main tasks of image processing is to distinguish between noise and actual contents so that the unwanted noise from the image signal can be removed
This paper proposes a new image denoising scheme using wavelet transformation
The experimental results show that our proposed scheme has better performance than the VisuShrink in terms of peak signal-to-noise ratio (PSNR) i.e., visual quality of the image
Summary
One of the main tasks of image processing is to distinguish between noise and actual contents so that the unwanted noise from the image signal can be removed. Several techniques using wavelet-based thresholding have been discussed in literature to reduce the noise from an image [1,2,3,4]. Donoho has proposed VisuShrink using hard and soft thresholding methods for image denoising [5,6,7]. This scheme exterminates many wavelet coefficients that might contain useful image information. We discuss a new image denoising scheme that performs better than the VisuShrink. We take three commonly used images in literature to establish the efficacy of our proposed method.
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