scholarly journals A Fast DCT Algorithm for Watermarking in Digital Signal Processor

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
S. E. Tsai ◽  
S. M. Yang
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Image ◽  
Spatial Data ◽  
Digital Signal Processor ◽  
Block Size ◽  
Digital Signal ◽  
Outer Product ◽  
Cosine Transform ◽  
Digital Image Compression ◽  
Inverse Dct

Discrete cosine transform (DCT) has been an international standard in Joint Photographic Experts Group (JPEG) format to reduce the blocking effect in digital image compression. This paper proposes a fast discrete cosine transform (FDCT) algorithm that utilizes the energy compactness and matrix sparseness properties in frequency domain to achieve higher computation performance. For a JPEG image of8×8block size in spatial domain, the algorithm decomposes the two-dimensional (2D) DCT into one pair of one-dimensional (1D) DCTs with transform computation in only 24 multiplications. The 2D spatial data is a linear combination of the base image obtained by the outer product of the column and row vectors of cosine functions so that inverse DCT is as efficient. Implementation of the FDCT algorithm shows that embedding a watermark image of 32 × 32 block pixel size in a 256 × 256 digital image can be completed in only 0.24 seconds and the extraction of watermark by inverse transform is within 0.21 seconds. The proposed FDCT algorithm is shown more efficient than many previous works in computation.

JPEG DCT Compressiom

2013 ◽  
Vol 712-715 ◽  
pp. 2542-2545
Author(s):  
Hong Li Jia ◽  
Qiang Liu
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Discrete Cosine Transform ◽  
Digital Image ◽  
Cosine Transform ◽  
Rapid Spread ◽  
Multimedia Technologies ◽  
Joint Photographic Experts Group ◽  
Digital Image Compression ◽  
Further Development

With the rapid spread of image processing applications and the further development of multimedia technologies, compression standards become more and more important. This paper intends to explain JPEG (Joint Photographic Experts Group) compression, which is currently a worldwide standard for digital image compression, is based on the discrete cosine transform (DCT). Based on the research, the paper describes theory and algorithms of the JPEG DCT compression and implements a baseline JPEG codec (encoder/decoder) with MATLAB.

scholarly journals An Efficient Image Watermarking Method Based on Fast Discrete Cosine Transform Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
S. E. Tsai ◽  
K. C. Liu ◽  
S. M. Yang
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Signal Processor ◽  
Transmission Loss ◽  
Image Watermarking ◽  
Digital Signal ◽  
Random Permutation ◽  
Cosine Transform ◽  
Two Dimensional Image ◽  
Host Image

This paper proposes an image watermarking method based on the fast discrete cosine transform (DCT) algorithm for implementation in digital signal processor. A digital watermark can be effectively embedded and efficiently extracted without the host image. The keys in watermarking process include four frequency coefficients in DCT, two random permutation vectors, and a quantization matrix for normalizing the watermark and the host image. The fast DCT algorithm has been shown to reduce the complexity of two-dimensional image transformation so that embedding/decoding an image watermark can be completed in real time within 0.33 seconds. The quality of both watermarked image and extracted (retrieved) watermark remains excellent. It is shown that the watermarking method is efficient in and robust to data cropping, transmission loss, and compression/decompression.

scholarly journals A Unified Algorithm for Subband-Based Discrete Cosine Transform

2012 ◽  
Vol 2012 ◽  
pp. 1-31 ◽  
Author(s):  
Lu-Ting Ko ◽  
Jwu-E Chen ◽  
Hsi-Chin Hsin ◽  
Yaw-Shih Shieh ◽  
Tze-Yun Sung
Keyword(s):  
Discrete Cosine Transform ◽  
System Performance ◽  
Linear Array ◽  
Signal To Noise Ratio ◽  
Reconfigurable Architecture ◽  
Signal To Noise ◽  
Cosine Transform ◽  
Unified Algorithm ◽  
Inverse Dct ◽  
Single Processor

Discrete cosine transform (DCT) and inverse DCT (IDCT) have been widely used in many image processing systems and real-time computation of nonlinear time series. In this paper, the unified DCT/IDCT algorithm based on the subband decompositions of a signal is proposed. It is derived from the data flow of subband decompositions with factorized coefficient matrices in a recursive manner. The proposed algorithm only requires(4(log2n)−1−1)and(4(log2n)−1−1)/3multiplication time forn-point DCT and IDCT, with a single multiplier and a single processor, respectively. Moreover, the peak signal-to-noise ratio (PSNR) of the proposed algorithm outperforms the conventional DCT/IDCT. As a result, the subband-based approach to DCT/IDCT is preferable to the conventional approach in terms of computational complexity and system performance. The proposed reconfigurable architecture of linear array DCT/IDCT processor has been implemented by FPGA.

A Dual Image Scrambling Method Based on Discrete Cosine Transform

2014 ◽  
Vol 556-562 ◽  
pp. 4722-4725
Author(s):  
Qiu Dong Sun ◽  
Jian Cun Zuo ◽  
Yu Feng Shao ◽  
Lin Gui
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Image ◽  
Original Image ◽  
Image Scrambling ◽  
Visual Evaluation ◽  
Space Domain ◽  
Cosine Transform ◽  
Inverse Discrete Cosine Transform ◽  
Dual Image ◽  
Arnold Transformation

Although the general random scrambling based on pixel can achieve a good chaotic effect, but it can not change the histogram of a digital image. We introduce the random scrambling into the domain of discrete cosine transform (DCT) of image and scramble the coefficients of DCT to improve the performance of scrambling. Firstly, we did 2-D discrete cosine transform to the original image. Secondly, we scanned the coefficients matrix of DCT by Zig-Zag scanning to get a 1-D sequence, and then we scrambled this sequence by 1-D random scrambling algorithm. Thirdly, we did inverse Zig-Zag scanning to the scrambled sequence and reconstructed the scrambled image from the chaotic coefficients matrix by 2-D inverse discrete cosine transform. Finally, to further improve the scrambling degree of the reconstructed result, we scrambled it again in space domain to gain the encryption image. Experiments show that this algorithm is effective at visual evaluation and is more stable in scrambling degree than Arnold transformation.

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