Performance Parameter Based Comparison of the Slantlet Transform and Discrete Cosine Transform (DCT) for Steganography in Biomedical Signals

2018 ◽  
pp. 81-89
Author(s):  
Apurwa S. Jagtap ◽  
Revati Shriram
Keyword(s):  
Discrete Cosine Transform ◽  
Performance Parameter ◽  
Cosine Transform ◽  
Biomedical Signals

LWT-DCT based Image Watermarking Scheme using Normalized SVD

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.

Fast odd discrete cosine transform algorithms

1990 ◽  
Vol 26 (8) ◽  
pp. 503
Author(s):  
S.C. Chan ◽  
K.L. Ho
Keyword(s):  
Discrete Cosine Transform ◽  
Cosine Transform

Systolic architecture for inverse discrete cosine transform

1995 ◽  
Vol 31 (21) ◽  
pp. 1809-1811 ◽  
Author(s):  
Yu-Tai Chang ◽  
Chin-Liang Wang
Keyword(s):  
Discrete Cosine Transform ◽  
Systolic Architecture ◽  
Cosine Transform ◽  
Inverse Discrete Cosine Transform

scholarly journals Asymmetric color image encryption and compression based on discrete cosine transform in Fresnel domain

2020 ◽  
Vol 1 ◽  
pp. 100005
Author(s):  
Eakta Kumari ◽  
Saurabh Mukherjee ◽  
Phool Singh ◽  
Ravi Kumar
Keyword(s):  
Discrete Cosine Transform ◽  
Image Encryption ◽  
Color Image ◽  
Color Image Encryption ◽  
Cosine Transform

scholarly journals Information hiding in images using Discrete Cosine Transform

2021 ◽  
Vol 1098 (5) ◽  
pp. 052083
Author(s):  
G Emmanuel ◽  
G G Hungil ◽  
J Maiga ◽  
A J Santoso
Keyword(s):  
Discrete Cosine Transform ◽  
Information Hiding ◽  
Cosine Transform
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