Papers by Keyword: Wavelet Transform (WT)

Abstract: Image compression is a data compression technology used in the digital image, its purpose is to reduce redundant information of the image data, and provide a more efficient format to store and transmit data. Due to the huge image data and the existing relatively low transport conditions, the image compression has become an inevitable. The key technology of image compression is how to transform image data, how to quantify image data, and how to entropy code the quantized data. Using two-dimensional Mallat image wavelet compression algorithm is a new method of image compression, and it is the core technology of the wavelet image compression.

Abstract: In order to get rid of noise from the angular displacement of the crank rocker mechanism, the wavelet transform method is introduced. After the noise corresponds to the high frequency band of wavelet domain of the signal and the signal corresponds to the low frequency band of wavelet domain of the signal, the signal is decomposed into four layers, and the high frequency brand is set zero. The test results show that this method was most ideal for the de-noising effect on displacement signals, which is able to not only retain valid signals but to effectively remove the noise.

Abstract: Digital watermarking is a new information security technology, and it uses the information to protect the security of multimedia data hiding technique. Digital watermarking in wavelet domain can make effective use of the human visual system characteristics, and can be compatible with the international compression standard, and the embedding watermark signal energy can be distributed to all of the pixel space. Based on the characteristic of multi-resolution wavelet decomposition and human visual system model matching, digital watermarking algorithm based on wavelet transform is proposed in this paper. The algorithm for tamper proof is designed by quantifying the significant wavelet coefficients to embed watermark sequence. Preprocessing and quantifying the image of this algorithm are studied, which resolves the rounding error and overflow problem brought by the watermarked image pixel values of wavelet transform. Through various attack test and analysis, the experimentation shows that it has strong robustness, can resist many common image attacks, and has strong practicability.

Abstract: With the increasing development of modern social information degree, the multimedia technology and network technology have rapid development, and the society puts forward new requirements for the education industry. Accordingly, this paper uses virtual design of Flash3D animation to development and design demonstration system of track and field action. The system uses the built-in method to extract the feature of track and field action, and uses the wavelet reconstruction algorithm to reconstruct the action, so as to achieve the function of action learning. We use Adobe Flash CS65 of the system to extract 5 groups of 1025 movements and reconstruct 10 groups of 2256 movements. Comparing the reconstructed image with the actual image frames, we found the new images reconstructed by the demonstration system are consisting with the real images frame. It provides a new computer method for teaching track and field action.

Abstract: Condition monitoring (CM) and fault diagnosis of equipments has gained greater attention in recent years, due to the need to reduce the down time and enhance the life/ condition of the equipments. The rolling element bearings (REB) are the most critical components in rotary machines. Hence, bearing fault detection and diagnosis is an integral part of the preventive maintenance activity. Vibration signal analysis provides wide range of information for analysis. So in this paper, vibration signals for four conditions of a deep groove ball bearing namely Normal (N), bearing with defect on inner race (IR), bearing with defect on ball (B), and bearing with defect on outer race (OR) have been acquired from a customized bearing test rig under maximum speed and variable load conditions. Depending on the machinery operating conditions and the extent of bearing defect severity, the measured vibration signals are non-stationary in nature. Non-stationary signals are effectively analyzed by wavelet transform technique, which is a popular and widely used time-frequency technique. The focus of this paper is to select a best possible mother wavelet for applying WT on bearing vibration signals. The two selection criteria includes minimum Shannon entropy criteria (MSEC) and Maximum Energy to Shannon Entropy Ratio criteria R(s). This helps in effective bearing CM using WT.

Abstract: Fuzzy clustering can express the ambiguity ofsample category, and better reflect the actual needs of datamining. By introducing wavelet transform and artificial immunealgorithm to fuzzy clustering, Wavelet-based Immune Fuzzy C-means Algorithm (WIFCM) is proposed for overcoming theimperfections of fuzzy clustering, such as falling easily into localoptimal solution, slower convergence speed and initialization-dependence of clustering centers. Innovations of WIFCM arethe elite extraction operator and the descent reproductive mode.Using the locality and multi-resolution of wavelet transform, theelite extraction operator explores the distribution and densityinformation of spatial data objects in multi-dimensional spaceto guide the search of cluster centers. Taking advantage ofthe relationship between the relative positions of elite centersand inferior centers, the descent reproductive mode obtains theapproximate fastest descent direction of objective function values,and assures fast convergence of algorithm. Compared to theclassic fuzzy C-means algorithm, experiments on 3 UCI data setsshow that WIFCM has obvious advantages in average numberof iterations and accuracy.

Abstract: In electric market, accurate electricity demand forecasting is often needed. Because electricity demand forecasting has become needful for creators and purchasers in the electric markets at present. But in electricity demand forecasting, noise signals, caused by various unstable factors, often corrupt demand series. In order to seek accurate demand forecasting methods, this article proposed a new combined electric load forecasting method (WSENN) which based on Wavelet Transform (WT), Seasonal Adjustment (SA) and Elman Neural Network (ENN) to forecast electricity demand. The effectiveness of WSENN is tested by applying the data from New South Wales (NSW) of Australia. Experimental results demonstrate that the WSENN model can offer more precise results than other methods that had mentioned in other literatures.

Abstract: Along with the development of the computer technology and the Internet, information hiding is given increasing attention. All kinds of the important information, such as government information, business information, personal privacy etc, should be transmitted safely. In the future, information hiding will play a very important role in the network to protect the information from damage. The content of this thesis is presented as follows: The analysis of the basic theory and concept of information hiding; The analysis and application of the space domain algorithms, transform (frequency) domain algorithm, etc focusing on the technology of digital watermarking, covert channel and anonymous communications. The theory of wavelet analysis and the experimental models are discussed deeply, basing on which the research and application of the wavelet is explored in the field of information hiding.

Abstract: An image-adaptive watermarking algorithm based on wavelet transform was proposed. At first, A digital image used as watermarking was scrambled. Next, the original image was decomposed by discrete wavelet transform,and in accordance with the characteristics of human visual system, wavelet decomposition in the low-frequency domain, Methods which average of adjacent domain instead of single wavelet decomposition coefficients was used to estimate and quantitative, watermarking was adaptively embedded in wavelet coefficients of low-frequency domain. At last, the simulation experimental results show that the algorithm for a variety of conventional image processing has good robustness.

Abstract: Hybrid optoelectronic joint transform correlator is a very effecitve tool to recognize a target, which has important application in military and industry field. However, in actual applications, under some situations, such as complex target background or insufficient contour information etc., the intensity of correlation peaks will be weak. Sometimes, the weak intensity of correlation peaks can not be recognized by joint transform correlator. Wavelet transform is adopted to process the joint target image. The principles of joint transform correlator and wavelet transform are given in this paper. As an actual example, a tank target is adopted to test the feasibility and effectiveness of this method. From computer simulation, we can get good experimental effect. After wavelet transform of joint target image, the intensity of correlation peaks has been increased obviously. Optical experiments confirm the feasibility and effectiveness of this method further. Amounts of experiments prove wavelet transform can extract the target contour effectively. Based on the principle of the proposed algorithm, the target recognizing rate can be increased to a higher level.