An Image Denoising Method Based on Improved Wavelet Thresholding. Issue 4 (December 2018)

• Record Type: Journal Article
• Authors: Qin, Chaoxuan; Gu, Xiaohui
• Is Part Of: IOP conference series. Volume 452:Issue 4(2018)
• Publication Date: 2018-12
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/452/4/042199
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: This paper proposes an improved-threshold function aimed to enhance the de-noising performance of wavelet thresholding method. Firstly, the theory of wavelet transforms and characteristic of soft-threshold function and hard-threshold function was introduced. Then, an improved-threshold function was proposed. The new method overcomes the discontinuous in hard threshold de-noising method and reduces the permanent bias in soft threshold de-noising method. Last, the improved-threshold algorithm, soft-threshold algorithm, hard-threshold algorithm, disperse wavelet transform (DWT) and wiener filtering are used to reduce the noise in the same image. The experiment result show that the improved-threshold algorithm can get a better denoising effect than the traditional soft and hard thresholding de-noising algorithms.