Earticle

Image denoising is a basic problem in image processing, fourth order partial differential equation model is an image denoising method proposed for maintaining the balance of denoising and edge keeping. But when the image is severely contaminated, the denoising effect is not ideal, it may fuzzes the boundary at the same time, this paper puts forward an improved fourth order partial differential equation model, in order to overcome the contradiction between denoising and edge keeping, better denoising effect is obtained, and through the numerical simulation the results show that the method has good stability and practical value.

Hyperspectral Image processing is usually time consuming, due to its huge data size. Nowadays Hyperspectral Imaging is used in many fields where real-time solutions are required. A systemic comparison study of linear feature extraction methods for classification of hyperspectral images with various types of noises is carried out in this paper, in which the performance of different linear feature extraction methods for classification and their computation cost reduction are compared. In practice, hyperspectral images are often contaminated by different types of noises, as the atmosphere around hyperspectral cameras may change all the time. In this paper, to make it more realistic, different types of noises, including Salt-and-Pepper noise, Gaussian noise, Speckle noise and their mixtures, are artificially imposed on the hyperspectral image. Support Vector Machine based classification is employed for classification performance comparison. The experimental results are very helpful for selecting linear feature extraction methods for classification of hyperspectral images that are usually affected with noises.

In modern life, we need better techniques based on biometric features recognition such as face recognition, fingerprint recognition and iris recognition. We present a method which can be used for face recognition or verification applications. The method can solve the problem that when the number of data categories is large and each number of the category used for training is small. As the conventional four stages, face detection, face alignment, face representation and face classification, we propose a Siamese architecture especially for the representation stage and use a one-against-one support vector machine for the classification stage. LFW dataset is used for training and testing which gets a considerable result. And we also test our system on other face dataset, which has a high accuracy on the recognition.

Subject in the process of image acquisition and the relative games between the camera or camera image fuzzy, it seriously affected the further image feature extraction, target recognition and image analysis. In order to meet the needs of reality, get high quality image, we must be used image restoration techniques for fuzzy image restoration. Based on the detailed study on the basis of the theory of wavelet transform, we confirmed by experiments in motion blurred image of wavelet and decomposition level .The method to identify the fuzzy parameters, under the condition of without noise and with noise on the four classic image restoration algorithm, the simulation experiment using the peak signal-to-noise ratio, mean square error, average gray level gradient method and Laplace operator method of four kinds of image quality evaluation index to evaluate the healing effect and recovery result diagram and its quality evaluation. Through the scene shooting motion blurred image point spread function of parameter identification and image restoration, it demonstrates that the proposed point spread function’s parameters identification method is sound and effective.

This survey attempts to provide a detailed overview of the previous work on Uyghur on-line handwritten character recognition technology and mainly focuses on investigating the feature extraction algorithms that have been presented or applied to Uyghur characters. Statistical, structural and combined-hybrid approaches for feature extraction technology for Uyghur characters are going to be explored. Besides the popular feature extraction methods which perhaps are granted to be taken into consideration for all letter kinds, the study on Uyghur handwritten recognition contributed new features and extraction algorithms for pattern recognition. Summarization on observing methods and extracted features from the published work and suggestions for further attempts would be valuable reference for the up-coming research activities on finding more efficient features.

In real-time collaborative graphical editing systems, Object-based Group/Ungroup operations are frequently accessible and practically useful. However, the existing research on these operations of the graphical editing is rare and defective. In this paper, based on Multi-Version strategy and Address Space Transformation method, a new MVSDR algorithm, which is not only applied to simple operations (such as Create, Delete, ChangeATT, etc.), but also suitable for Group/Ungroup ones, is proposed to solve the consistency maintenance problem. The proposed algorithm abandons previous attempts to divide conflict operations into Real-Conflict operations and Resolvable-Conflict ones and to deal with them separately, thus making the algorithm more simple and effective. In addition, an example analysis is also given in this paper to prove the algorithm’s correctness and effectiveness.

This paper presents the enhancement of speech signals in a noisy environment based on Wavelet Based Adaptive filtering (WAF). In this technique, the speech signals contaminated with noise are processed through the WAF. The adaptive algorithm based on least squares, updates the weighting factors of the filter to keep the difference between input and desired signal at a minimum level to eliminate the unwanted noise and interferences. The performance of the proposed method is evaluated by computing the Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), Root-Mean-Square-Error (RMSE), Percentage Root Mean Square Difference (PRD) after denoising. The investigation on speech signals contaminated by noise has demonstrated that the performance of the proposed method is stable and reliable in the noisy environment.

We presented a survey on High-dynamic-range imaging (HDRI or HDR) is a set of methods used in the imagingand photography to reproduce a superior dynamic range of luminosity than regular digital imaging or photographic methods can do. HDR images can denote a superior range of the luminance levels than can be attained using the extra 'classical' techniques. Images such as those holding many actual-world scenes, from same bright and direct sunlight to dangerous shade or very faint nebulae. It is the often succeeded in catching and then joining numerous dissimilar exposures of the similar subject matter. A Non-HDR cameras take a photograph with some limited amount of exposure range, as finally resulting in the damage of the detail in bright or dark parts. In this paper, we are studying about HDR image, generating of HDR image and also study about image fusion and methods of image fusioning.

In this study, we address the problem of multi-person detection and tracking in challenging scenes using sparse stereo information. In each frame, only a sparse set of object feature points are extracted. All these feature points are then projected onto a plan-view map, and grouped into several clusters by employing the biometric information, the optical flow information of object feature points, as well as the width of a person. By producing clusters, the location of a possible person can be determined. In addition, a Modified Joint Probabilistic Data Association Filter (MJPDAF) is proposed for improving the performance of measurements association during the people tracking process. Compared to the traditional JPDAF, the methods for the construction of the validation matrix and the calculation of association probabilities are improved. Experiments on challenging datasets demonstrate that the proposed algorithm is robust for people detection and tracking through fixed stereo vision.

This paper presents a literature survey on Digital Watermarking within an image. It describes the early work carried out on digital watermarks, including the brief analysis of various watermarking schemes and its applications. This paper also makes a comparison between various watermarking schemes .This paper also gives us a brief introduction about the procedure of digital watermarking.

Physical Uplink Control Channel (PUCCH) is an important narrow-band channel in LTE-Advanced system, which carries the uplink control information, such as acknowledge/non-acknowledge (ACK/NACK) bits, downlink channel quality indicator (CQI), HARQ-ACK feedback information, and it requires much higher transmission quality than the other channels. With the aid of orthogonal CDMA, multiple users share the same time-frequency resource, the multiuser interference has been the main factor that limits the transmission quality of the control information [1]. In the high-speed mobile scenario, there exists a large Doppler frequency shift, which leads to loss of code orthogonality and also introduces inter-carrier interference (ICI) within a single SC-FDMA symbol. Besides, the multiuser interference in high-speed mobile environment is severe. In this paper, the carrier frequency offset estimation algorithms are analyzed, and a double-iteration carrier frequency offset (CFO) estimation algorithm is proved to perform the best for PUCCH Format 1 in high-speed mobile scenario. The estimation process is achieved by coarse estimation and fine estimation, which enlarges the estimation range and improves the estimation accuracy.

This study proposes a feasible method for spectral color reproduction based on a node address array selection technique from CIE tristimulus values. In this method three-dimensional lookup table (3-D LUT) has been constructed to connect the node address array and the spectrum as the source and destination spaces. First we present a general framework for how to reproduce spectral color. Then results of recovery are evaluated by the root mean square error (RMSE) and the color difference CIE ΔE00. According to the results considered, the proposed method could reconstruct the spectral reflectance with a high spectral and colorimetric accuracy.

Often some noise signals get interleaved with speech signals and owing to noisy surroundings the captured signal may not sound as desired. For such cases, a combination of Hilbert transform filter and Biquad filter in cascaded form might prove helpful. An arrangement in a simulink model demonstrates successful noise reduction in a voice signal recorded from a microphone. Both the filters used were of Direct Form structure, while the Hilbert filter was a Direct Form FIR, the Biquad was Direct Form II structure filter. The observations for speech signal as well as noise signals have been produced as results that show a significant noise removal.

In complicated scene, in order to solve the temporal occlusion problem of target tracking, a novel particle filter tracking algorithm based on graphical model is proposed. Graphical model is applied to particle filtering in this method. Firstly, dividing the target into several key regions, and extracting the characteristic value of each region. Then, these regions are applied to construct graphical model. In the process of target tracking by using particle filter method, graphical models can compensate for the lacking information of the occluded region. The state of the occluded part can be inferred by the graphical model. Finally, experimental results have demonstrated that the proposed tracking algorithm is effective, and it can reliably track moving target.

A 4th-Order low-distortion low-pass ΣΔ modulator structure is proposed in this paper, which uses the timing-sharing between the 3rd and 4th integrators during one clock phase. Compared with conventional cascade of integrators with distributed feed-forward (CIFF) sigma-delta modulator structure, the proposed structure not only solves the critical timing issue for the quantizer and feedback DAC path, but also eliminates an extra active adder to sum up the input feed-forward. By methods of delay redistribution structure, the time for quantization and feedback dynamic element match (DEM) operation can be extended from a non-overlapping interval for a conventional low-distortion structure to half of the sampling clock period. Capacitive input feed-forward (CIF) methodology eliminates the adder in front of the quantizer. Further, the op-amp of the last integrator is used as an active adder by op-amp sharing. Therefore, the power consumption can be reduced and the linearity of the feedback DAC is improved because of the increasing time which used for implementation of DEM algorism. The proposed 4th-Order low-distortion low-pass ΣΔ modulator with 4-bit quantizer is simulated in MATLAB. From the simulation results, the proposed structure can achieve a peak SNR (signal- to-noise ratio) of 87dB with 2.5MHz bandwidth under 32 oversampling ratio at 160MHz sampling frequency and the ENOB of 14.234bits in non-ideal condition.

There has been tremendous advancement in the field of computing in the last two decades. Human face is the most dominant characteristic which is used to verify/authenticate a person amongst group of people. Face detection technology is developed for detecting facial features and ignores background images or cluttered images. Computer-based face recognition system has revolutionized the way the world works around these days, as government agencies (law and justice enforcement) are readily accepting this technology as a standard method for recognizing the uniqueness in a human beings [1]. Our proposed system is based on facial recognition that can be used by Delhi Metro System for easing up the process of fare calculation deduction system by means of automating the system using cameras placed at the entry gate, inside the metro rail and at the exit gate. This system will help in saving the man hours required for vending out tokens/ tickets/ smart cards in the metro system. This system will also increase the accuracy and will help in replacing traditional fare calculation activity which is perform daily.

For image denoising and enhancement, we combine dyadic wavelet transform and hidden Markov tree (HMT) model, and propose an image edge enhancement method based on dyadic wavelet domain hidden Markov models and interpolation algorithm. Making use of scale correlation between HMT model and binary wavelet coefficients, we establish different interpolation classification for different pixel distribution, realize enhanced image through transforming low resolution picture into high resolution picture, and simplify the complexity of computing at the same time. The simulation results show that compared with dyadic wavelet transform, both visual effects and quantitative analysis has significantly improved by wavelet domain HMT model method.

In this paper, main is analyzing the technical actions to limit and expand the characteristics numerical distance relay protection in order to reduce losses and improve functioning protection, and considering the specifications, efficiency and losses of the backup stages distance relay protection on high-voltage lines. Addition to this, criterion technical efficiency of back-up stage distance relay protection is presented. Based on these analysis and criterion, recommendations for designing and setting backup stages distance relay protection are proposed.

Infrasonic wave is the usually sound wave caused by vibrating body at frequency below 20Hz, which is commonly found in a variety of industry, transportation, nature and living environment. This paper designs a high precision infrasonic sound sensor based on PVDF, which is a new piezoelectric material of macromolecule with piezoelectric property. The research results proved that when a given frequency values between 3Hz to 30Hz, the proposed sensor has good performance and high precision, which could meet the design requirements, and has a certain practical value.

In this paper, we present a face and gesture based human computer interaction (HCI) system. We combine head pose and hand gesture to control the system. We can identify the positions of the eyes and mouth, and use the face center to estimate the pose of the head. Moreover, we introduce a technique for automatic gesture area segmentation and orientation normalization of the hand gesture. The user does not need to keep gestures in upright position and the system segments and normalizes the gestures automatically. The experimental results show that the proposed approach is accurate with gesture recognition rate of 93.6%. Also, the user can control multiple devices, including robots simultaneously through a wireless network.

Automatic brain tumor segmentation from multispectral magnetic resonance imaging (MRI) data is an important but a challenging task because of the high diversity in the appearance of tumor tissues among different patients and in many cases similarity with the normal tissues. In this paper, we propose a fully automatic technique for brain tumor segmentation from multispectral human brain MRIs. We first use the intensities of different patches in multispectral MRIs to represent the features of both normal and abnormal tissues and generate a dictionary for following tissue classification. Then, the sparse representation classification (SRC) is applied to classify the brain tumor and normal brain tissue in the whole image. At last, the Markov random field (MRF) regularization introduces spatial constraints to the SRC to take into account the pair-wise homogeneity in terms of classification labels and multispectral voxel intensities. Our method was evaluated on 20 multi-modality patient datasets with competitive segmentation results.

In allusion to the shortcomings of the existing signal analysis method for high-frequency analysis, non-stationary signal analysis and so on, wavelet analysis and grey theory are introduced into the signal analysis, a new signal analysis method based wavelet analysis and grey theory is proposed in this paper. In this method, the wavelet packet is used to nonredundantly, lossless and orthogonally decompose different components of noise signals into different frequency bands with different scales, in order to realize the signal frequency band division with total energy conservation for obtaining the energy feature of each frequency band. Then these energy frequency bands are used to construct the feature vector. And the grey theory is used to analyze the correlation degree between the equipment states and system parameters in order to quickly and accurately determine the position of source. Finally, for a typical signal simulation and analysis, the effectiveness of the signal method is tested and verified.

Images include information about human body which is used for different purposes such as medical, security and other plans. Compression of images is used in some applications such as profiling data and transmission systems. Regard to importance of images information, lossless or lossy compression is preferred. Lossless compressions are JPEG, JPEG-LS and JPEG 2000 is few well-known methods for lossless compression. We will use differential pulse code modulation for image compression with Huffman encoder, which is one of the latest and provides good compression ratio, peak signal noise ratio and minimum mean square error. In real time application which needs hardware implementation, low complex algorithm accelerates compression process. In this dissertation, we use differential pulse code modulation for image compression lossless and near-lossless compression method is introduced which is efficient due to its high compression ratio and simplicity. This method is consists of a new transformation method called Enhanced DPCM Transformation (EDT) which has a good energy compaction and a suitable Huffman encoding. After introduce this compression method, it is apply on different images from Corel dataset for experimental results and analysis. As well we compare it with other existing methods with respect to parameter compression ratio, peak signal noise ratio and mean square error.

Wavelet denoising is a commonly used method in the field of image denoising algorithms, based on the analysis of the characteristics of estimated wavelet coefficients in the wavelet threshold denoising and the traditional soft threshold and hard threshold method, in the light of the discontinuity of hard threshold and fixed deviation of soft threshold, and non-differentiable of compromise algorithm, a wavelet threshold denoising algorithm is put forward which is continuous based on the wavelet coefficients and differentiable and variable threshold value deviation, the experimental results show that this method has better denoising effect and has good practical value.

A method of structure lane detection and departure based on inverse perspective mapping (IPM) and effective gradient points is proposed. Firstly, road image is transformed into plan view using inverse perspective transform to eliminate perspective effect. Secondly, “Sobel” operator and morphological image processing are used to detect edge and eliminate noise. According to the actual lane width, effective gradient points are extracted. Finally, lane is fitted using the least square method. Experimental results show that the method can detect both sides lane and analyze departure and lane detection rate is 97.5%. The method can provide reference for lane departure warning system.

Long Term Evolution-Advanced (LTE-A) has brought revolution in the field of wireless communication technology by providing high data rates of up to 1Gbps. One key enhancement feature of LTE-A is bandwidth extension by the use of multi-carrier technology to support deployment bandwidth of up to 100MHz. To achieve such high data rate in IMT-Advanced mobile systems, carrier aggregation technology by 3GPP has been introduced to support very-high-data rate transmissions over wide frequency bandwidth in the new LTE-Advanced standards. This work includes the details of Downlink LTE Advanced System Model and thereby all the performance analysis of Non Contiguous Carrier Aggregation are done and an overview of LTE-Advanced CA scenarios is discussed. Also component carrier parameters and oversampling factor are found and using these parameters power spectrum is plotted. The main outcome from this work is increase in the throughput of the system by increasing the number of carrier components or by increasing bandwidth. Many proposals on carrier aggregation in LTE-A have been published but still there is a need of research to be carried out in this field as this technology has not fully matured.

Camera calibration is the basis for realization of image distortion correction. Because the causes of image distortion are very complex, it has become a difficulty to correct image distortion with calibration results. In order to reduce the complexity of the existing distortion correction method, an eight parameters camera calibration model was proposed in this paper. In this model, eight parameters were used in describing radial distortion and tangential distortion. The experimental results show that the proposed method can be easily solved and correct distortion accurately.