Phases under Gaussian Additive Noise

被引：0

作者：

Panigrahi, Susant Kumar ^{[1
]}

Gupta, Supratim ^{[1
]}

Sahu, Prasanna K. ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Elect Engn, Rourkela, India

来源：

2016 INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP), VOL. 1 | 2016年

关键词：

Additive Gaussian noise; Dual tree complex wavelets transform; Fast Discrete Curvelet transform; and Peak Signal to Noise Ratio; Structural similarity index measure; IMAGE; INFORMATION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The phase of complex transforms like Fourier, Complex wavelet and curvelet of an image is more immune to noise than its magnitude. This article analyses its immunity to additive white Gaussian noise (AWGN) both mathematically and quantitatively. We have derived noise sensitivity (i.e. the rate of change of noisy image phase or magnitude with respect to AWGN magnitude) and used Structural Similarity Index Measure (SSIM) and Peak Signal to Noise Ratio (PSNR) to quantify its effects. The results indicate that the magnitude of these transforms deteriorates faster than that of phase with increasing noise strength. The noise sensitivity of phases for different transforms is compared. It is observed that the wavelet phase retains more structural similarity while the curvelet phase is more immune to noise.

引用

页码：1771 / 1776

页数：6

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