Efficient Denoising by Feature Recovery from Residual Noise in Spatial Domain

  • et al.
N/ACitations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The growth of image processing techniques has lead to limitless applications of imaging in various fields of medical, remote sensing. However, the unpreventable problem of noise contamination arises during the processing of images. As the noise content in an image rises, it becomes difficult to denoise an image while preserving high-frequency edge features as well as low frequency smooth features. Minimal artefacts and better preservation of geometrical details such as edges and texture reflects efficient image reconstruction. Since many State-of-the-art denoising algorithms have been reported in the literature, and there is always a compromise between noise removal and feature preservation. A novel approach for efficient noise removal along with recovery of fine features is being proposed. The idea behind denoising approach is the use of hybridization of spatial domain filters where base layer image and residual image are extracted and processed separately to mitigate the prevalence of artefacts and preserve image content. The performance of the proposed method is evaluated both quantitatively as well as qualitatively, and it is found that the proposed method could outperform existing denoising techniques.

Cite

CITATION STYLE

APA

Girdher*, A. … Budhiraja, S. (2019). Efficient Denoising by Feature Recovery from Residual Noise in Spatial Domain. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 947–957. https://doi.org/10.35940/ijrte.d7604.118419

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free