Runlength encoding of quantized discrete cosine transform (DCT) coefficients

1995 ◽  
Author(s):  
Viresh Ratnakar ◽  
Ephraim Feig ◽  
Eric Viscito ◽  
Sudhakar Kalluri
Keyword(s):  
Discrete Cosine Transform ◽  
Cosine Transform ◽  
Dct Coefficients

A Novel Hybrid Discrete Cosine Transform Speeded Up Robust Feature-Based Secure Medical Image Watermarking Algorithm

2020 ◽  
Vol 10 (11) ◽  
pp. 2588-2599
Author(s):  
Saqib Ali Nawaz ◽  
Jingbing Li ◽  
Uzair Aslam Bhatti ◽  
Anum Mehmood ◽  
Raza Ahmed ◽  
...  
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Watermarking ◽  
Copyright Protection ◽  
Image Watermarking ◽  
Image Feature ◽  
Feature Descriptor ◽  
Cosine Transform ◽  
Speeded Up Robust Features ◽  
Feature Based ◽  
Dct Coefficients

With the advancement of networks and multimedia, digital watermarking technology has received worldwide attention as an effective method of copyright protection. Improving the anti-geometric attack ability of digital watermarking algorithms using image feature-based algorithms have received extensive attention. This paper proposes a novel robust watermarking algorithm based on SURF-DCT perceptual hashing (Speeded Up Robust Features and Discrete Cosine Transform), namely blind watermarking. We design and implement a meaningful binary watermark embedding and extraction algorithm based on the SURF feature descriptor and discrete-cosine transform domain digital image watermarking algorithm. The algorithm firstly uses the affine transformation with a feature matrix and chaotic encryption technology to preprocess the watermark image, enhance the confidentiality of the watermark, and perform block and DCT coefficients extraction on the carrier image, and then uses the positive and negative quantization rules to modify the DCT coefficients. The embedding of the watermark is completed, and the blind extraction of the watermark realized. Correlation values are more than 90% in most of the attacks. It provides better results against different noise attacks and also better performance against rotation. Transparency and high computational efficiency, coupled with dual functions of copyright protection and content authentication, is the advantage of the proposed algorithm.

scholarly journals Efficient Image Cipher Based on Baker Map in the Discrete Cosine Transform

2020 ◽  
Vol 20 (1) ◽  
pp. 68-81
Author(s):  
Hesham Alhumyani
Keyword(s):  
Discrete Cosine Transform ◽  
Experimental Tests ◽  
Differential Sensitivity ◽  
Cosine Transform ◽  
Chaotic Baker Map ◽  
Image Cipher ◽  
Plain Image ◽  
Dct Coefficients ◽  
Inverse Dct ◽  
Baker Map

AbstractThis paper presents an efficient image cipher based on applying the chaotic Baker Map (BM) in the Discrete Cosine Transform (DCT). The encryption module of the proposed DCT-based BM image cipher employs a DCT on the original plain-image then, the DCT coefficients of the plain-image are shuffled with the BM. Finally, the inverse DCT is applied to the shuffled plain-image DCT coefficients to obtain the final cipher-image. The decryption module of the proposed DCT-based BM image cipher employs a DCT on the input cipher-image then, the DCT coefficients of the cipher-image are inversely shuffled with the BM. Finally, the inverse DCT is applied to the inversely shuffled cipher-image DCT coefficients to obtain the original plain-image. A set of experimental tests are performed to test the validity of the proposed DCT-based BM image cipher and the performed tests demonstrated the superiority of the proposed DCT-based BM image cipher in terms of statistical, differential, sensitivity and noise immunity.

Face Recognition System using Discrete Cosine Transform combined with MLP and RBF Neural Networks

2012 ◽  
Vol 4 (4) ◽  
pp. 11-35 ◽  
Author(s):  
Fatma Zohra Chelali ◽  
Amar Djeradi
Keyword(s):  
Neural Networks ◽  
Face Recognition ◽  
Discrete Cosine Transform ◽  
Recognition Rate ◽  
Recognition System ◽  
Rbf Neural Networks ◽  
Cosine Transform ◽  
Linear Discriminant ◽  
Face Recognition System ◽  
Dct Coefficients

Proposed is an efficient face recognition algorithm using the discrete cosine transform DCT Technique for reducing dimensionality and image parameterization. These DCT coefficients are examined by a MLP (Multi-Layer Perceptron) and radial basis function RBF neural networks. Their purpose is to present a face recognition system that is a combination of discrete cosine transform (DCT) algorithm with a MLP and RBF neural networks. Neural networks have been widely applied in pattern recognition for the reason that neural-networks-based classifiers can incorporate both statistical and structural information and achieve better performance than the simple minimum distance classifiers. The authors demonstrate experimentally that when DCT coefficients are fed into a back propagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. Comparison with other statistical methods like Principal component Analysis (PCA) and Linear Discriminant Analysis (LDA) is presented. Their face recognition system is tested on the computer vision science research projects and the ORL database.

scholarly journals Keamanan Pesan Rahasia Menggunakan Steganografi DCT (Discrete Cosine Transform) pada Citra JPEG

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Dian Hafidh Zulfikar
Keyword(s):  
Discrete Cosine Transform ◽  
Spatial Domain ◽  
Cover Image ◽  
Secret Message ◽  
Least Significant Bit ◽  
Cosine Transform ◽  
Secret Information ◽  
Dct Coefficients ◽  
Lsb Technique ◽  
Dct Coefficient

<p class="SammaryHeader" align="center"><strong><em>Abstract</em></strong><em></em></p><p><em> </em>The  least significant-bit (LSB) based techniques are very popular for steganography in spatial domain. The simplest LSB technique simply replaces the LSB in the cover image with the  bits from secret information. Further advanced techniques use some criteria to identify the pixels in which LSB(s) can be replaced with the bits of secret information. In Discrete Cosine Transform (DCT) based technique insertion of secret information in carrier depends on the DCT coefficients. Any DCT coefficient value above proper threshold is a potential place for insertion of secret information.</p><p class="Abstrak"><strong> </strong><strong>Keywords :</strong> Discrete Cosine Transform (DCT), steganography, secret message</p><p><strong><em> </em><em>Abstra</em><em>k</em></strong></p><p>Pada steganografi domain spasial, teknik least significant-bit (LSB) merupakan teknik yang paling banyak digunakan pada steganografi. Teknik yang sederhana yang hanya mengubah nilai LSB pada cover image dengan nilai bit pesan rahasia, atau dengan teknik yang lebih baik lagi yaitu dengan menentukan bit-bit LSB mana yang akan dilakukan pergantian nilai bit. Lain halnya dengan metode Discrete Cosine Transform (DCT), teknik steganografi ini akan menyembunyikan informasi rahasia tergantung dari nilai Koefisien DCT.</p><p class="Abstrak"> </p><p class="Abstrak"><strong>Kata Kunci :</strong> Steganografi, DCT, Citra, JPEG, Pesan Rahasia</p>

scholarly journals Efficient Security Based Video Watermarking Technique using Chaotic Encryption with Discrete Cosine Transform

2019 ◽  
Vol 8 (6) ◽  
pp. 1416-1427
Keyword(s):  
Discrete Cosine Transform ◽  
Digital Video ◽  
Video Watermarking ◽  
Chaotic Encryption ◽  
Median Filtering ◽  
Arnold Transform ◽  
Cosine Transform ◽  
Digital Video Watermarking ◽  
Proposed Model ◽  
Dct Coefficients

In this paper, a novel chaotic encryption-based blind digital video watermarking technique (DVWT) is presented for grayscale and color images. This method makes use of Discrete Cosine transform (DCT) prior to embed the watermark in the hosting video. The hosting video is split into frames of 8*8 nonoverlapping blocks before employing DCT, and watermark bit is implanted by altering the variations among the nearby DCT coefficients of neighboring blocks. Arnold transform is applied for chaotic encryption to offer extra security to the watermark. A set of three versions of the proposed model has been applied and the results are investigated. The experimental outcome confirms that the DCT-VWT is efficient on different image processing functions such as JPEG compression, sharpening, cropping, and median filtering. The comparative analysis ensures that the presented DCT for digital video watermarking technique (DCT-DVWT) is efficient under subjective as well as objective way.

scholarly journals USING ARTIFICIAL NEURAL NETWORKS FOR TIME DIFFERENCE OF ARRIVAL TARGET LOCALIZATION BASED ON REDUCED DISCRETE COSINE TRANSFORM

2019 ◽  
Vol 16 (33) ◽  
pp. 530-540
Author(s):  
T. SHEVGUNOV
Keyword(s):  
Neural Networks ◽  
Discrete Cosine Transform ◽  
Time Difference ◽  
Target Localization ◽  
Delay Estimation ◽  
Time Difference Of Arrival ◽  
Cosine Transform ◽  
Dct Coefficients ◽  
Artificial Neural ◽  
Hidden Layer

The angular coordinates of the pulse source are determined by comparing the signals received simultaneously on several channels. To solve this issue, the application of neural networks is highly important. In this article, the application of the artificial neural network (ANN) approach to the task of target localization is discussed. The research was performed on the basis of a feature extraction technique executed by a discrete cosine transform, which allowed to obtain a compact representation of the signal energy subjected to digital processing. The author defines the angle-of-arrival estimation scheme based on time difference of arrival estimators and the particular problem of estimating constant delays as informative parameters embedded into received signals that are noisy and damped copies of the reference signal. The adaptive element framework is used for synthesis of the feedforward ANN which is fed with the reduced set of the most sensitive discrete cosine transform (DCT) coefficients, which provide a concise representation of the first-order cyclostationary random process. The investigation on the delay estimation accuracy has been carried out to evaluate the performance of the ANNs with different size of their hidden layer and various numbers of the DCT coefficients at their input. It has been proved that five DCT coefficients are enough for the discrimination of the phase shift in the whole range. In turn, it results in the reliable delay estimation produced by the trained ANN that contains eight neurons in its hidden layer.

scholarly journals Time-Domain Blind ICI Compensation in Coherent Optical FBMC/OQAM System

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6397
Author(s):  
Binqi Wu ◽  
Jin Lu ◽  
Mingyi Gao ◽  
Hongliang Ren ◽  
Zichun Le ◽  
...  
Keyword(s):  
Phase Noise ◽  
Discrete Cosine Transform ◽  
Time Domain ◽  
Phase Error ◽  
Transmission System ◽  
Cosine Transform ◽  
Noise Compensation ◽  
Decision Error ◽  
Dct Coefficients ◽  
The Time Domain

A blind discrete-cosine-transform-based phase noise compensation (BD-PNC) is proposed to compensate the inter-carrier-interference (ICI) in the coherent optical offset-quadrature amplitude modulation (OQAM)-based filter-bank multicarrier (CO-FBMC/OQAM) transmission system. Since the phase noise sample can be approximated by an expansion of the discrete cosine transform (DCT) in the time-domain, a time-domain compensation model is built for the transmission system. According to the model, phase noise compensation (PNC) depends only on its DCT coefficients. The common phase error (CPE) compensation is firstly performed for the received signal. After that, a pre-decision is made on a part of compensated signals with low decision error probability, and the pre-decision results are used as the estimated values of transmitted signals to calculate the DCT coefficients. Such a partial pre-decision process reduces not only decision error but also the complexity of the BD-PNC method while keeping almost the same performance as in the case of the pre-decision of all compensated signals. Numerical simulations are performed to evaluate the performance of the proposed scheme for a 30 GBaud CO-FBMC/OQAM system. The simulation results show that its bit error rate (BER) performance is improved by more than one order of magnitude through the mitigation of the ICI in comparison with the traditional blind PNC scheme only aiming for CPE compensation.

scholarly journals An Improved Robust and Adaptive Watermarking Algorithm Based on DCT

2012 ◽  
Vol 10 (3) ◽  
Author(s):  
Q. Zhang ◽  
Y. Li ◽  
X. Wei
Keyword(s):  
Discrete Cosine Transform ◽  
Chaotic System ◽  
Jpeg Compression ◽  
Experimental Results ◽  
Stego Image ◽  
Embedding Method ◽  
Cosine Transform ◽  
Adaptive Watermarking ◽  
Adaptive Embedding ◽  
Dct Coefficients

This paper proposes an improved watermarking algorithm based on DCT(Discrete Cosine Transform). We carried out the algorithm as described as follows. First, we extended both rows and ranks of the watermark by using the proposed method before the embedding stage. After expansion, Sine chaotic system is employed in encrypting the watermark. In the embedding stage, an effective and adaptive embedding method is proposed to embed the watermark into the blocked DCT coefficients. Experimental results demonstrate that the proposed algorithm in this paper works well in resisting both geometry attack and noise attack. It also does well in recovering the watermark after stego image suffered from JPEG compression.

POPULAR DCT MODELS

2007 ◽  
Vol 05 (05) ◽  
pp. 725-733 ◽  
Author(s):  
SARALEES NADARAJAH ◽  
SAMUEL KOTZ
Keyword(s):  
Discrete Cosine Transform ◽  
Bayesian Approach ◽  
Laplace Distribution ◽  
Natural Images ◽  
Superior Performance ◽  
Cosine Transform ◽  
Dct Coefficients ◽  
Dct Coefficient

It is well known that the distribution of the discrete cosine transform (DCT) coefficients of most natural images follows a Laplace distribution. In this note, using a Bayesian approach, we derive two popular models for the distribution of the actual DCT coefficient. We illustrate the superior performance of these models over the standard Laplace model.

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