Spatially-varying blur kernel measurement based on discrete cosine transform single-pixel imaging

2019 ◽  
Author(s):  
Hongzhi Jiang ◽  
Yu Wang ◽  
Huijie Zhao ◽  
Xudong Li ◽  
Yang Xu ◽  
...  
Keyword(s):  
Discrete Cosine Transform ◽  
Cosine Transform ◽  
Blur Kernel ◽  
Spatially Varying Blur ◽  
Spatially Varying ◽  
Single Pixel

scholarly journals High Performance Discrete Cosine Transform Operator Using Multimedia Oriented Subword Parallelism

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Shafqat Khan ◽  
Emmanuel Casseau ◽  
Daniel Menard
Keyword(s):  
Discrete Cosine Transform ◽  
Resource Utilization ◽  
High Performance ◽  
Multimedia Applications ◽  
Utilization Rate ◽  
Two Dimensional ◽  
Cosine Transform ◽  
Subword Parallelism ◽  
Speed Up ◽  
Single Pixel

In this paper an efficient two-dimensional discrete cosine transform (DCT) operator is proposed for multimedia applications. It is based on the DCT operator proposed in Kovac and Ranganathan, 1995. Speed-up is obtained by using multimedia oriented subword parallelism (SWP). Rather than operating on a single pixel, the SWP-based DCT operator performs parallel computations on multiple pixels packed in word size input registers so that the performance of the operator is increased. Special emphasis is made to increase the coordination between pixel sizes and subword sizes to maximize resource utilization rate. Rather than using classical subword sizes (8, 16, and 32 bits), multimedia oriented subword sizes (8, 10, 12, and 16 bits) are used in the proposed DCT operator. The proposed SWP DCT operator unit can be used as a coprocessor for multimedia applications.

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
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