Improved variable ZA-LMS algorithm based on discrete cosine transform for high noise reduction

Acoustic pyrometry is a comparatively advanced method of temperature measurement developed in recent years, which possesses the essential characteristics of traditional temperature measurement approach. Considering the interferences, like strong background noise, reverberation and so on, in boiler furnace, the LMS (least mean square) adaptive filter algorithm should be improved to meet certain environment above. In order to make the LMS algorithm have the characteristic of fast convergence and small steady state error, an improved, power-normalized and variable step-size discrete cosine transform LMS algorithm is proposed, which combines the power-normalized discrete cosine transform LMS algorithm with the variable step size LMS algorithm that uses the sliding forgetting-weighted window. The time delay estimation simulation in the strong-noise environment verifies the improved DCT-MVSS LMS algorithm can achieve good performance.

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Variable Step-size LMS Algorithm Based on Discrete Cosine Transform for Voice Signal Denoising

DEStech Transactions on Computer Science and Engineering ◽

10.12783/dtcse/aicae2019/31474 ◽

2019 ◽

Author(s):

Zhuo CHEN

Keyword(s):

Discrete Cosine Transform ◽

Lms Algorithm ◽

Variable Step Size ◽

Signal Denoising ◽

Step Size ◽

Cosine Transform ◽

Voice Signal ◽

Variable Step

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Improved LMS Adaptive Algorithm and its Application of Time Delay Estimation in Power Plant

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.668-669.699 ◽

2014 ◽

Vol 668-669 ◽

pp. 699-702

Author(s):

Shi Ping Zhang ◽

Guo Qing Shen ◽

Lian Suo An

Keyword(s):

Time Delay ◽

Discrete Cosine Transform ◽

Time Delay Estimation ◽

Lms Algorithm ◽

Delay Estimation ◽

Variable Step Size ◽

Step Size ◽

Boiler Furnace ◽

Cosine Transform ◽

Variable Step

Time delay estimation plays an important role in accuracy of leakage location in industrial boiler furnace. Considering about interference, like strong background noise, reverberation and so on, in boiler furnace, the LMS (least mean square) adaptive filter algorithm should be improved to meet certain environment above .In order to makes the LMS algorithm have the characteristic of fast convergence and small steady state error, an improved, power-normalized and variable step-size discrete cosine transform LMS algorithm is proposed, which combines the power-normalized discrete cosine transform LMS algorithm with the variable step size LMS algorithm that uses sliding forgetting-weighted window . The time delay estimation simulation in the strong-noise environment verifies the improved DCT-MVSS LMS algorithm can achieve good performance.

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Wavelet domain-based video noise reduction using temporal discrete cosine transform and hierarchically adapted thresholding

IET Image Processing ◽

10.1049/iet-ipr:20060223 ◽

2007 ◽

Vol 1 (1) ◽

pp. 2 ◽

Cited By ~ 6

Author(s):

N. Gupta ◽

M.N.S. Swamy ◽

E.I. Plotkin

Keyword(s):

Noise Reduction ◽

Discrete Cosine Transform ◽

Wavelet Domain ◽

Cosine Transform

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Channel Estimation Scheme with Low-Complexity Discrete Cosine Transform in MIMO-OFDM System

IEICE Transactions on Communications ◽

10.1587/transcom.e92.b.3836 ◽

2009 ◽

Vol E92-B (12) ◽

pp. 3836-3842

Author(s):

Daisuke TAKEDA ◽

Yasuhiko TANABE

Keyword(s):

Channel Estimation ◽

Discrete Cosine Transform ◽

Low Complexity ◽

Ofdm System ◽

Cosine Transform ◽

Estimation Scheme ◽

Mimo Ofdm

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Investigation of the Adaptive Discrete Cosine Transform Technique for Still Picture Data Compression

10.21236/ada228745 ◽

1989 ◽

Author(s):

DELTA INFORMATION SYSTEMS INC HORSHAM PA

Keyword(s):

Data Compression ◽

Discrete Cosine Transform ◽

Cosine Transform

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LWT-DCT based Image Watermarking Scheme using Normalized SVD

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200821161656 ◽

2020 ◽

Vol 13 ◽

Author(s):

Rahul Dixit ◽

Amita Nandal ◽

Arvind Dhaka ◽

Vardan Agarwal ◽

Yohan Varghese

Keyword(s):

Wavelet Transform ◽

Singular Value Decomposition ◽

Discrete Cosine Transform ◽

Image Watermarking ◽

Singular Value ◽

Cover Image ◽

Lifting Wavelet Transform ◽

Cosine Transform ◽

Lifting Wavelet ◽

Value Decomposition

Background: Nowadays information security is one of the biggest issues of social networks. The multimedia data can be tampered with, and the attackers can then claim its ownership. Image watermarking is a technique that is used for copyright protection and authentication of multimedia. Objective: We aim to create a new and more robust image watermarking technique to prevent illegal copying, editing and distribution of media. Method : The watermarking technique proposed in this paper is non-blind and employs Lifting Wavelet Transform on the cover image to decompose the image into four coefficient matrices. Then Discrete Cosine Transform is applied which separates a selected coefficient matrix into different frequencies and later Singular Value Decomposition is applied. Singular Value Decomposition is also applied to the watermarking image and it is added to the singular matrix of the cover image which is then normalized followed by the inverse Singular Value Decomposition, inverse Discrete Cosine Transform and inverse Lifting Wavelet Transform respectively to obtain an embedded image. Normalization is proposed as an alternative to the traditional scaling factor. Results: Our technique is tested against attacks like rotation, resizing, cropping, noise addition and filtering. The performance comparison is evaluated based on Peak Signal to Noise Ratio, Structural Similarity Index Measure, and Normalized Cross-Correlation. Conclusion: The experimental results prove that the proposed method performs better than other state-of-the-art techniques and can be used to protect multimedia ownership.

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