Artificial neural network based wavelet transform technique for image quality enhancement. (June 2019)

• Record Type: Journal Article
• Authors: Vimala, C.; Priya, P. Aruna
• Is Part Of: Computers & electrical engineering. Volume 76(2019)
• Page Start: 258
• Page End: 267
• Publication Date: 2019-06
• Subjects: Image denoising -- Discrete wavelet transform -- Artificial neural network -- Peak signal-to-noise ratio -- Root mean-square error; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.04.005
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Image quality enhancement is an important image processing task, wherein denoising an image is essential for accurate image diagnoses, because the presence of noise in an image produces incorrect information. This paper proposes double density wavelet transform based intelligent techniques for image denoising. This hybrid technique combines wavelet and neural networking methods, performed and validated using different standard images and extant denoising methods. These images were degraded using a variety of noise levels to simulate actual noise degradation. The results reveal the high-peak signal-to-noise ratio of the proposed system, which is thus considered effective compared to state-of-the-art techniques.