Results 271 to 280 of about 133,828 (342)

On Computing the Discrete Cosine Transform

IEEE Transactions on Computers, 1978
Haralick has shown that the discrete cosine transform of N points can be computed more rapidly by taking two N-point fast Fourier transforms (FFT's) than by taking one 2N-point FFT as Ahmed had proposed. In this correspondence, we show that if Haralick had made use of the fact that the FFT's of real sequences can be computed more rapidly than general ...
Ben-Dau Tseng, William C. Miller
openaire   +2 more sources

New image blind watermarking method based on two-dimensional discrete cosine transform

, 2020
In this paper, a new image blind watermarking method based on two-dimensional Discrete Cosine Transform (2D-DCT) is presented to realize copyright protection of color image.
Zihan Yuan, Decheng Liu, Xueting Zhang, Qingtang Su   +3 more
semanticscholar   +1 more source

A robust copy-move forgery detection technique based on discrete cosine transform and cellular automata

Journal of Information Security and Applications, 2020
Copy Move Forgery (CMF) is a type of digital image forgery in which an image region is copied and pasted to another location within the same image with malicious intent to misrepresent its meaning.
Gulnawaz Gani, F. Qadir
semanticscholar   +1 more source

Discrete cosine transform filtering

Signal Processing, 1990
Circular convolution-multiplication relationships for the discrete cosine transform (DCT) that are similar to those for the discrete Fourier transform (DFT) are developed. The relations are valid if the filter frequency response is real and even. Two fairly simple relations are developed.
Bowonkoon Chitprasert, K. R. Rao 0001
openaire   +1 more source

Unsupervised band selection based on weighted information entropy and 3D discrete cosine transform for hyperspectral image classification

International Journal of Remote Sensing, 2020
Band selection is an effective means of reducing the dimensionality of the hyperspectral image by selecting the most informative and distinctive bands.
S. Sawant, P. Manoharan
semanticscholar   +1 more source

Reversible discrete cosine transform

Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), 2002
In this paper a reversible discrete cosine transform (RDCT) is presented. The N-point reversible transform is firstly presented, then the 8-point RDCT is obtained by substituting the 2 and 4-point reversible transforms for the 2 and 4-point transforms which compose the 8-point discrete cosine transform (DCT), respectively.
Kunitoshi Komatsu, Kaoru Sezaki
openaire   +1 more source

A Fast Image Fusion With Discrete Cosine Transform

IEEE Signal Processing Letters, 2020
A fast and effective image fusion method based on discrete cosine transform (DCT) is proposed. The fusion quality and computation time of current DCT-based image fusion methods largely depend on the selected block size, and the selection of the block ...
Monan Wang, Xiping Shang
semanticscholar   +1 more source

A Deep Learning Approach in the Discrete Cosine Transform Domain to Median Filtering Forensics

IEEE Signal Processing Letters, 2020
This letter presents a novel median filtering forensics approach, based on a convolutional neural network (CNN) with an adaptive filtering layer (AFL), which is built in the discrete cosine transform (DCT) domain.
Jun Zhang, Yixin Liao, Xinshan Zhu, Hongquan Wang, Jie Ding   +4 more
semanticscholar   +1 more source

Binary Discrete Cosine and Hartley Transforms

IEEE Transactions on Circuits and Systems I: Regular Papers, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saad Bouguezel, M. Omair Ahmad, M. N. S. Swamy 0001   +2 more
openaire   +2 more sources

DctViT: Discrete Cosine Transform meet vision transformers

Neural Networks
Vision transformers (ViTs) have become one of the dominant frameworks for vision tasks in recent years because of their ability to efficiently capture long-range dependencies in image recognition tasks using self-attention.
Keke Su, Lihua Cao, Botong Zhao, Ning Li, Di Wu, Xiyu Han, Yangfan Liu   +6 more
semanticscholar   +1 more source