一种基于DCT的图像多描述编码方法

多描述编码针对不可靠网络传输将信号源编码成多个比特流,利用信号冗余估计丢失的信息,支持多层次质量解码。就两个描述的情况提出了三种基于离散余弦变换(DCT)的多描述编码方案。

DCT domain filtering method for multi-antenna code acquisition

For global navigation satellite system （GNSS） signals in Gaussian and Rayleigh fading channel, a novel signal detection algorithm is proposed. Under the low frequency uncertainty case, after performing discrete cosine transform （DCT） to the outputs of the partial matched filter （PMF） for every antenna, the high order com- ponents in the transforming domain will be filtered, then the equalgain （EG） combination for the inverse discrete cosine transform （IDCT） reconstructed signal would be done subsequently. Thus, due to the different frequency distribution characteristics between the noise and signals, after EG combination, the energy of signals has almost no loss and the noise energy is greatly reduced. The theoretical analysis and simulation results show that the detection algorithm can effectively improve the signal-to-noise ratio of the captured signal and increase the probability of detection under the same false alarm probability. In addition, it should be pointed out that this method can also be applied to Rayleigh fading channels with moving antenna.

Adaptive Image Digital Watermarking with DCT and FCM

A novel adaptive digital image watermark algorithm is proposed. Fuzzy c-means clustering （FCM） is used to classify the original image blocks into two classes based on several characteristic parameters of human visual system （HVS）. One is suited for embedding a digital watermark, the other is not. So the appropriate blocks in an image are selected to embed the watermark. The wetermark is embedded in the middle-frequency part of the host image in conjunction with HVS and discrete cosine transform （DCT）. The maximal watermark strength is fixed according to the frequency masking. In the same time, for the good performance, the watermark is modulated into a fractal modulation array. The simulation results show that we can remarkably extract the hiding watermark and the algorithm can achieve good robustness with common signal distortion or geometric distortion and the quality of the watermarked image is guaranteed.

Low complexity DCT-based distributed source coding with Gray code for hyperspectral images

To compress hyperspectral images, a low complexity discrete cosine transform （DCT）-based distributed source coding （DSC） scheme with Gray code is proposed. Unlike most of the existing DSC schemes, which utilize transform in spatial domain, the proposed algorithm applies transform in spectral domain. Set-partitioning-based approach is applied to reorganize DCT coefficients into waveletlike tree structure and extract the sign, refinement, and significance bitplanes. The extracted refinement bits are Gray encoded. Because of the dependency along the line dimension of hyperspectral images, low density paritycheck-（LDPC）-based Slepian-Wolf coder is adopted to implement the DSC strategy. Experimental results on airborne visible/infrared imaging spectrometer （AVIRIS） dataset show that the proposed paradigm achieves up to 6 dB improvement over DSC-based coders which apply transform in spatial domain, with significantly reduced computational complexity and memory storage.

A NEW LBG-BASED IMAGE COMPRESSION METHOD USING DCT

In this letter, a new Linde-Buzo-Gray (LBG)-based image compression method using Discrete Cosine Transform (DCT) and Vector Quantization (VQ) is proposed. A gray-level image is firstly decomposed into blocks, then each block is subsequently encoded by a 2D DCT coding scheme. The dimension of vectors as the input of a generalized VQ scheme is reduced. The time of encoding by a generalized VQ is reduced with the introduction of DCT process. The experimental results demonstrate the efficiency of the proposed method.

AN IMPROVED ALL ZERO BLOCK FINDING METHOD BASED ON THE STATISTIC CHARACTERISTICS OF DCT TRANSFORM COEFFICIENTS

In the H.263 video codec related systems, motion estimation and Discrete Cosine Transform (DCT) have the most computational requirements. In order to reduce complexity of the encoder to dedicate more resources to other functions, according to the study of existing methods, an Improved All Zero Block Finding (IAZBF) method based on the statistic characteristics of DCT coefficients is proposed. Compared with existing methods, IAZBF improves the detecting efficiency by about 50% without importing too much extra computation requirement. Being computed with additions and shifts instead of complicated multiplications, IAZBF is of low computation complexity, especially for low-end processors. In addition, IAZBF upholds picture fidelity and remains compatible with the H.263 bitstream standard.

A method to compress vibration signals using wavelet packet transformation combined with sub-band vector quantization

A novel compression method for mechanical vibrating signals,binding with sub-band vector quantization(SVQ) by wavelet packet transformation(WPT) and discrete cosine transformation(DCT) is proposed.Firstly,the vibrating signal is decomposed into sub-bands by WPT.Then DCT and adaptive bit allocation are done per sub-band and SVQ is performed in each sub-band.It is noted that,after DCT,we only need to code the first components whose numbers are determined by the bits allocated to that sub-band.Through an actual signal,our algorithm is proven to improve the signal-to-noise ratio(SNR) of the reconstructed signal effectively,especially in the situation of lowrate transmission.

A Review of Image Steganography Based on Multiple Hashing Algorithm

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

Vehicle detection method for expressway by MPEG compressed domain

A method which extracts traffic information from an MPEG-2 compressed video is proposed. According to the features of vehicle motion, the motion vector of a macro-block is used to detect moving vehicles in daytime, and a filter algorithm for removing noises of motion vectors is given. As the brightness of the headlights is higher than that of the background in night images, discrete cosine transform （DCT）coefficient of image block is used to detect headlights of vehicles at night, and an algorithm for calculating the DCT coefficients of P-frames is introduced. In order to prevent moving objects outside the expressway and video shot changes from disturbing the detection, a driveway location method and a video-shot-change detection algorithm are suggested. The detection rate is 97.4% in daytime and 95.4% in nighttime by this method. The results prove that this vehicle detection method is effective.

ASIC Design of DA-Based 2-D Inverse Discrete Cosine Transform

Aim To present an ASIC design of DA based 2 D IDCT. Methods\ In the design of 1 D IDCT is utilized a Chen based fast IDCT algorithm, and multiplier accumulators based on distributed algorithm contributes in reducing the hardware amount and in enhancing the speed performance. Results and Conclusion\ VHDL simulation, synthesis and layout design of system are implemented. This 2 D IDCT ASIC design owns best timing performance when compared with other better designs internationally. Results of design prove to be excellent.

视觉单通道唇读系统的有效性

在建立视觉单通道的大词汇量唇读系统中,提出了归一化的U-LDCT-KL两级唇读特征提取方法,即针对唇区分块的DCT(Discrete Cosine Transform)系数进行二级KL(Karhunen-Loeve Transform)去局域参数的交叠。此方法一方面提取了唇读的最有效的低级语义特征,另一方面更加合理地选择利用了特征的有效可区分性,使得用42维二级视觉特征,对特定人的唇动内容识别正确率达到77.8%。实验还证明了系统中分块的唇区DCT特征对的视觉单通道唇读系统是最有效的。

Watermarking of Digital Images in Frequency Domain

Invisible watermarking methods have been applied in frequency domains, trying to embed a small image inside a large original image. The original bitmap image will be converted into frequency domain to obtain the discrete cosine transform （DCT） matrices from its blocks. The bits of the logo image are embedded in random color components of the original image, as well as in random positions in each selected block. These positions are alternating current （AC） coefficients of the DCT matrix. The randomness is obtained from RC4 pseudorandom bit generator that determines in which color component this logo image bits will be embedded. The embedded bits have been hidden in random blocks in the image, which are chosen according to a （semi-random） function proposed in this work.

A new all-zero 4×4 block determination rule for integer transform and quantization in AVS-M encoder

A new all-zero block determination rule was used to reduce the complexity of the AVS-M encoder. It reuses the sum of absolute difference of 4x4 block obtained from motion estimation or intra prediction as parameters so that the determination threshold need to be computed only once when quantization parameter (QP) is invariable for given video sequence. This method avoids a lot of computation for transform, quantization, inverse transform, inverse quantization and block reconstruction. Simulation results showed that it can save about 20%～50% computation without any video quality degradation.

Hybrid Machine Learning Model for Face Recognition Using SVM

Face recognition systems have enhanced human-computer interactions in the last ten years.However,the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations.Principal Component Analysis-Support Vector Machine(PCA-SVM)and Principal Component Analysis-Artificial Neural Network(PCA-ANN)are among the relatively recent and powerful face analysis techniques.Compared to PCA-ANN,PCA-SVM has demonstrated generalization capabilities in many tasks,including the ability to recognize objects with small or large data samples.Apart from requiring a minimal number of parameters in face detection,PCA-SVM minimizes generalization errors and avoids overfitting problems better than PCA-ANN.PCA-SVM,however,is ineffective and inefficient in detecting human faces in cases in which there is poor lighting,long hair,or items covering the subject’s face.This study proposes a novel PCASVM-based model to overcome the recognition problem of PCA-ANN and enhance face detection.The experimental results indicate that the proposed model provides a better face recognition outcome than PCA-SVM.

Weak GPS signal acquisition method based on DBZP

Double block zero padding(DBZP) is a widely used but costly method for weak global positioning system(GPS) signal acquisition in software receivers. To improve the computational efficiency, this paper proposes an algorithm based on the differential DBZP algorithm and the discrete cosine transform(DCT) domain filtering method. The proposed method involves using a differential correlator after the DBZP operation. Subsequently, DCT domain low pass filtering(LPF) and inverse DCT(IDCT) reconstruction are carried out to improve the signal to noise ratio(SNR). The theoretical analysis and simulation results show that the detection algorithm can effectively improve the SNR of the acquired signal and increase the probability of detection under the same false alarm probability.

An Improved Image Watermark Algorithm

An improved Image watermark algorithm(IIWA) is given in this paper, the with flow chart and the work principle of this algorithm are introduced in detail Although the normal watermarking technique brings up a new way of securing data transactions through the Internet, its robustness and integrity are vulnerable during the net transmission and image processing Using network signature technique, varied coding methods and other unique technique, IIWA improved the general watermark algorithm in the robustness and integrity in other words, IIWA greatly enhanced the transmission security and can be applied to information protection in the Internet

Lexicographic Image Hash Based on Space and Frequency Features

A lexicographic image hash method based on space and frequency features was proposed. At first, the image database was constructed, and then color and texture features were extracted from the image blocks including information for every image in the database, which formed feature vectors. The feature vectors were clustered to form dictionary. In hash generation, the image was preproc^ssed and divided into blocks firstly. Then color and texture features vectors were extracted from the blocks. These feature vectors were used to search the dictionary, and the nearest word in dictionary for each block was used to form the space features. At the same time. frequency feature was extracted from each block. The space and frequency features were connected to form the intermediate hash. Lastly, the final hash sequence was obtained by pseudo-randomly permuting the intermediate hash. Experiments show that the method has a very low probability of collision and a good perception of robustness. Compared with other methods, this method has a low collision rate.

The Implementation of Mirror-Image Effect in MPEG-2 Compressed Video

Straightforward techniques for spatial domain digital video editing (DVE) of compressed video via decompression and recompression are computationally expensive. In this paper, a novel algorithm was proposed for mirror-image special effect editing in compressed video without full frame decompression and motion estimation. The results show that with the reducing of computational complexity, the quality of edited video in compressed domain is still close to the quality of the edited video in uncompressed domain at the same bit rate.

Image enhancement and post-processing for low resolution compressed video

This research paper recommends the point spread function(PSF)forecasting technique based on the projection onto convex set(POCS)and regularization to acquire low resolution images.As the environment for the production of user created contents(UCC)videos(one of the contents on the Internet)becomes widespread,resolution reduction and image distortion occurs,failing to satisfy users who desire high quality images.Accordingly,this research neutralizes the coding artifact through POCS and regularization processes by:1)factoring the local characteristics of the image when it comes to the noise that results during the discrete cosine transform(DCT)and quantization process;and 2)removing the blocking and ring phenomena which are problems with the existing video compression.Moreover,this research forecasts the point spread function to obtain low resolution images using the above-mentioned methods.Thus,a method is suggested for minimizing the errors found among the forecasting interpolation pixels.Low-resolution image quality obtained through the experiment demonstrates that significant enhancement was made on the visual level compared to the original image.

ADAPTIVE RECONSTRUCTION TECHNIQUE FOR THE LOST INFORMATION OF THE RECTANGULAR IMAGE AREA

The adaptive reconstruction for the lost information of the rectangular image area is very important for the robust transmission and restoration of the image. In this paper, a new reconstruction method based on the Discrete Cosine Transform (DCT) domain has been put forward. According to the low pass character of the human visual system and the energy distribution of the DCT coefficients on the rectangular boundary, the DCT coefficients of the rectangular image area are adaptively selected and recovered. After the Inverse Discrete Cosine Transform (IDCT), the lost information of the rectangular image area can be reconstructed. The experiments have demonstrated that the subjective and objective qualities of the reconstructed images are enhanced greatly than before.