Lifting Filter Research Articles

Computer Augmented Reality Model-Based Interactive Teaching System for Chinese Line Drawing CAD

To achieve automatic target region detection, an interactive image segmentation technique has been always used as preferences. However, when it comes to the implementation of computer aided design, there is a problem with the structured method. The technique of stroke contour extraction based on boundary detection is used in this investigation. The high-frequency lifting filter improves the original image, and the grey scale and spatial distribution of the pixels are used to determine how the pixels are distributed on the pen track. The segmentation of mural lines and strokes is achieved well in a limited space. To ascertain each pixel's grey value distribution, a non-realistic rendering technique is suggested. Draw in accordance with the boundary tangential flow and each pixel's category. In conclusion, the two approaches can cover more application scenarios and yield good results in the extraction of creative materials from Chinese classical mural painting while maintaining the entire shape of the original strokes in the painting.

A novel design of low-cost hearing aid devices using an efficient lifting filter bank with a modified variable filter

ABSTRACT Objectives In recent years, audio signal processing begins its outbreak on a global scale, which has altered the global market and has rapidly extended out as a fundamental design in various industries. Lifting based method is frequently implemented in many applications such as image processing and audio processing because it has some advantages that faster implementation with minimum computational cost. Methods In this proposed work, a Novel Lifting based Filter Bank (NLFB) is proposed using a modified variable filter aimed at digital hearing aid devices. This filter bank design has some mandatory constraints, such as hardware complexity, power consumption, and delay. The proposed method is designed with four lifting steps such as split, predict, update and merge to make the perfect reconstruction in analysis and decomposition in synthesis bank. The performance analysis of the proposed method is discussed in this article. Results The proposed method consumes less power, up to 45mW, and a minimum delay between 85ns and 91.1ns when compared to traditional methods. Conclusion The proposed design output consumes 32 % of minimum hardware components, 12% of low power compared to interpolated filter bank and 6% of delay is reduced using Modified Variable Filter (MVFB).

Hardware Efficient Hybrid Encoder for Video Surveillance Application

Extensive use of digital multimedia has led to the development of advance video processing techniques for development of multimedia applications. Application such as video surveillance requires 247 recording and streaming. So, the bandwidth and storage costs become significant. With introduction of video streaming over internet, where different kinds of end users request same content with different available bandwidth, it requires scalable video coding (SVC). These challenges can be overcome by developing new techniques to reduce redundancy in subsequent frames and to improve the coding efficiency. In this paper, overlapping weighted linear sum (OWLS) pre-processing method and its hardware architecture are proposed. It is implemented using field progrmmable gate array (FPGA) and the application specific integrated circuit (ASIC) is also developed using TSMC180nm technology standard cell library. Results show improvement in terms of power and area as compared to the existing work. In motion compensated temporal filtering (MCTF), wavelet transform is implemented by temporal filters. Architecture for 5/3 Lifting MCTF is also implemented and compared with baseline H.264 video codec. Simulation results show that the average peak signal to noise ratio (PSNR) improvement is 2.36[Formula: see text]dB. The MCTF design using 5/3 Lifting filter is synthesized for Virtex-5 FPGA and compared with the existing close-loop architecture with better performance.

Detection of Bearing Faults Using a Novel Adaptive Morphological Update Lifting Wavelet

The current morphological wavelet technologies utilize a fixed filter or a linear decomposition algorithm, which cannot cope with the sudden changes, such as impulses or edges in a signal effectively. This paper presents a novel signal processing scheme, adaptive morphological update lifting wavelet (AMULW), for rolling element bearing fault detection. In contrast with the widely used morphological wavelet, the filters in AMULW are no longer fixed. Instead, the AMULW adaptively uses a morphological dilation-erosion filter or an average filter as the update lifting filter to modify the approximation signal. Moreover, the nonlinear morphological filter is utilized to substitute the traditional linear filter in AMULW. The effectiveness of the proposed AMULW is evaluated using a simulated vibration signal and experimental vibration signals collected from a bearing test rig. Results show that the proposed method has a superior performance in extracting fault features of defective rolling element bearings.

Salt-and-pepper noise removal by adaptive median-based lifting filter using second-generation wavelets

In this paper, we propose a novel adaptive median-based lifting filter for image de-noising which has been corrupted by homogeneous salt and pepper noise. The median-based lifting filter removes the noise of the input image by calculating the median of the neighboring significant pixels. The algorithm for image noise removal uses the lifting scheme of the second-generation wavelets in conjunction with the proposed adaptive median-based lifting filter. The experimental results demonstrate the efficiency of the proposed method. The proposed algorithm is compared with all the basic filters, and it is found that our method outperforms many other algorithms and it can remove salt and pepper noise with a noise level as high as 90%. The algorithm works exceedingly well for all levels of noise, as illustrated in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) measures.

Self-lifting scheme: new approach for generating and factoring wavelet filter bank

The authors presents a new lifting scheme, the self-lifting scheme, and prove that self-lifted wavelets based on orthogonal or biorthogonal wavelets remain biorthogonal. In contrast to self-lifting, the existing lifting scheme can be called cross-lifting. Compared with cross-lifting, the self-lifting scheme provides new approaches for constructing biorthogonal wavelets, as well as factorising wavelet filter bank (WFB). For constructing wavelets, the self-lifting-based method updates one part of a wavelet filter by the other part of the same filter and obtains two updated filters in one pass, whereas the cross-lifting based method updates one filter by another filter and obtains one updated filter in one pass. To factorise WFB, self-lifting takes one part of a filter as the factor to decompose the other part of the same filter and obtains two factorised filters in one pass, whereas cross-lifting based one takes one part of a filter as the factor to decompose the corresponding part of the other filter and obtains one factorised filter in one pass. Several examples show how to use self-lifting scheme to produce new wavelets with desirable properties, how to factorise complex WFBs into simple lifting filter banks, how to implement self-lifting-based discrete wavelet transform (WT) in z-domain and in time domain and why lifting-based WT is superior to convolution-based one.

Condition monitoring of linear guideways using a matched wavelet approach

The success of discrete wavelet methods for pattern matching applications can be significantly increased by finding a wavelet that closely approximates the pattern of interest. However, the process of fitting a wavelet to a given pattern is non-linear and non-trivial. In this paper we will address two problems. First, we develop and analyze an analytic approach for constructing a family of discrete wavelets that is optimally fitted to a given pattern. The construction is based on computing a suitable lifting filter. Secondly, we apply this matched wavelet approach to detect defects in linear guideways. Results with real data from acoustic measurements of such defects illustrate the potential of this approach.

Efficient lifting wavelet transform for microprocessor and VLSI applications

Recently, wavelet analysis has gained an established role in signal and image processing applications. In this paper, we present a discrete wavelet transform algorithm based on the lifting scheme. The Haar wavelet transformed and decimated signals are lifted by the ladder-type network. A unique lifting filter is designed for in-place computation. The present algorithm is especially suitable for microprocessor and VLSI applications since it can be implemented by integer arithmetics using only register shifts and summations.