Earticle

Based on traditional wavelet image denoising model, studies the quaternion, the application of wavelet transform in image denoising, quaternions are given three on the wavelet transform domain image denoising model and algorithm: (1) based on quaternion wavelet hidden markov tree model of image denoising; (2) based on quaternion wavelet transform non-gaussian bivariate distribution image denoising algorithm of bayesian statistical model; (3) based on quaternion mixing statistical model of wavelet image denoising. Experiments show that: in this paper, the denoising effect of these methods, in both the peak signal-to-noise ratio and the visual effects are better than many classic denoising algorithms.

The traditional image completion algorithms based on patches, are to iteratively search the most similar patches in the known region of the whole image to fill the target region. Generally, it is difficult to use these algorithms in practice, due to the big computation. To overcome this problem, in this paper we propose a novel image completion algorithm based on partial regions. Firstly we adapt a randomized correspondence algorithm to search the pixels in the known region that are similar with the pixels in the border of the target region. Then the regions that include the main structures and Texture can be determined by these pixels, and thus we can limit the search space. Secondly we optimize the method of computing filling priorities that is based confidence factor and edge information. Consequently, the correctness of the order of the repairing patches and the success of structures propagation have been enhanced. Finally we improve the method of calculating the most similar patches. A variety of experiments show that, in general, our method yields better results and is 5-10 times faster than the state-of-the-art methods.

Now a day’s Harmonic distortion has been a significant problem to maintain power quality. It is very essential to analyze of power signal and find different harmonics. Some harmonics in the power signals are harmful to sensitive equipments and also causes to power loss. It is therefore important to find such harmonics and use different harmonic mitigation techniques to get clean/pure signal for safe operation of the connected equipments and minimize Power loss. Harmonic distortion is the corruption of the fundamental sine wave at frequencies that are multiples of the fundamental. Aim of this paper is extraction of fundamental and harmonic components in voltage/current signal using FFT & STFT, plot the stylized spectrum of distorted signal in MATLAB with power system frequency and classify the subtypes of harmonics, study the different characteristics and calculate total harmonic distortion (THD) that will be useful for solving problems related to power quality.

For large complex electromechanical products, cable digital design has a problem of low accuracy because of its large deformable characteristics. To solve the problem, an efficacious method is proposed to do cable geometry physical modeling, simulation and test for two-end constrained spatial flexible cables. Euler angles are used as generalized parametric variables to describe cable configuration on the base of Kirchhoff elastic rod theory. Via establishment of a cylindrical coordinate system according to Saint-Venant principle using end constraint, Euler angles’ Analytical solutions of the Kirchhoff equations are gained. Based on an open source geometry kernel system and using numerical integration ideas, a cable configuration simulation platform is developed in C++ environments. Then, a cable geometry measurement bench is founded with the use of 3D laser scan technology. Finally, a cable configuration simulation and experimental example is given to verify the accuracy of the proposed model and relative algorithm, through 3D positional deviation analysis.

In Compressed Sensing (CS) framework, reconstruction of a signal relies on the knowledge of the sparse basis & measurement matrix used for sensing. Most of the studies so far focus on the application of CS in fields of images, radar, astronomy and Speech. This paper introduce new sensing matrix called orthogonal Symmetric Toeplitz Matrix (OSTM) generated with Binary, Ternary and PN sequence and shows detailed comparison of them with DCT Basis applied on 8 KHz sampled speech signal. Also it shows improved results of OSTM compared to Random, Bernoulli, Hadamard and Fourier Matrices. Performance of sensing matrices has been compared with Mean square error, Signal to noise ratio and Perceptual Evaluation of Speech Quality (PESQ) parameters.

Shot boundary detection is used to summarize the video in the video content management system so that particular content or required scene can be extracted from a given video and also observers or users can easily find summary of the given video in short time instead of time spending in seeing full length video. Also shot boundaries can be used for video indexing, browsing, and retrieval. So to extract such key frames (shot boundaries) from a given video needs a robust technique with high accuracy and low error rate. In this research work, we proposed a robust technique to find shot boundary using feature vectors, which are obtained from features calculated for each sub-band in the contour let transform domain. The feature vector has the energy, standard deviation, and histogram similarity as the features of each sub-band. The experimental results proved that this novel and robust method had more accuracy rate and low error rate.

SIFT (Scale invariant feature transform) descriptor is one of the most effective local features that is used for scale, rotation and illumination invariant of automatic image registration. In this paper a fast bi-directional matching algorithm based on SIFT was proposed for improving match accuracy and reducing match time. Firstly the single-feature points and multi-feature points in two images were extracted, and then matched all these feature points respectively by using the BBF (Best Bin First)-based bi-directional matching algorithm. The integrated matching correspondences were the final matches. The experimental results showed that the proposed algorithm can reduce mismatch probability and decrease the matching time.

New trends are more essential in the area of video enhancement for various emerging needs. Hence, we proposed a novel technique which efficiently suited for various types videos. This paper discussed about the video enhancement aiming to achieve high intra frame and inter frame qualities in an entire video. We proposed and evaluated two parameters i.e., Intra frame quality (among the frames) of the entire video and inter frame quality (in between the frames) of the entire video. Such as multiple regions of interest that can be adaptively and simultaneously enhanced. Two steps were incorporated in to the proposed work for object quality retrieval. These are (i) ACB step improve intra frame analysis features for region-of-interest a global tone curve is created by fusing from other region and (ii) ECB step improve inter frame quality implement by histogram equalization method. We observed better improvement in PSNR values and considerable reduction in MSE values over the existing techniques. Thus, the modified technique improves the video enhancement with respect to the countable number of frames and valid better results at various levels of frames. We also evaluated the execution time in the process of video enhancement which is the ultimate parameter to discuss the power consumption. The observations of the proposed technique surpass the existing methods in the area of video enhancement in frame by frame procedure. The results of the proposed technique outperform present techniques and werre simulated using MATLAB.

Caption region detection is significant for text segmentation and recognition in video images. In this paper, caption region detection includes the following three steps: text corner detection, candidate text region generation, non-text region elimination. Firstly, an improved Harris corner detection algorithm based on second difference, called sHarris, is proposed to detect text corners. sHarris detector is effective to detect text corners existing in video image. Secondly, morphologic operations are utilized to generate candidate text regions after text corner points are detected. Finally, non-text regions are eliminated from candidate text regions by some validation rules. In the end of this paper, experiments are used to analyze and evaluate the detection results of caption regions, which indicate the effectiveness of the proposed method.