Mapping of Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) based on Symmetries

2003 ◽  
Vol 49 (1) ◽  
pp. 35-42 ◽  
Author(s):  
S Poornachandra ◽  
V Ravichandran ◽  
N Kumaravel
2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
S. Akhter ◽  
V. Karwal ◽  
R. C. Jain

Fast windowed update algorithms capable of independently updating the odd discrete cosine transform (ODCT) and odd discrete sine transform (ODST) of a running data sequence are analytically developed. In this algorithm, to compute the ODCT coefficients of a real-time sequence, we do not require the ODST coefficients. Similarly, the ODST coefficients of the shifted sequence can be calculated without using ODCT coefficients. The running input data sequence is sampled using a rectangular window. However, this idea can be easily extended for other windows. The update algorithm derived herein can be used to compute the transform coefficients of the shifted sequence as new data points are available. The complexity of developed algorithm isO(N). The validity of algorithm is tested by MATLAB simulations.


1995 ◽  
Vol 31 (21) ◽  
pp. 1811-1812 ◽  
Author(s):  
Jiun-In Guo ◽  
Chein-Wei Jen ◽  
Chingson Chen

Author(s):  
Rahul Dixit ◽  
Amita Nandal ◽  
Arvind Dhaka ◽  
Vardan Agarwal ◽  
Yohan Varghese

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.


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

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