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Wavelet thresholding techniques are becoming popular in the signal processing community for denoising applications. Near-minimax properties were in particular established for simple threshold estimates over wide classes of regular functions. In this paper, we establish close connections between wavelet thresholding techniques and MAP estimation using exponential power prior distributions for a wide...
Wavelet transforms have been utilised effectively for image denoising, providing a means to exploit the relationships between coefficients at multiple scales. In this paper, a modified structure is presented that enables the utilisation of an unlimited number of wavelet filters. An alternative denoising technique is thus proposed with a simple approach for the utilisation of multiple wavelet filters...
Geochemical data processing plays an important role in the process of geochemical prospecting. According to the nonlinear characteristics of the geochemical data, the wavelet adaptive multi-threshold based on generalized cross-validation (GCV) criterion was adopted towards geochemical data preprocessing and good results are also achieved by validation in practical work area.
Successful implementation of type-1 Fuzzy Systems (FS) in diverse application areas have been accomplished till date. Nonetheless type-1 FS are not able to handle significant amount of uncertainties present in dynamic real world applications. An improved performance against these uncertainties is achieved by type-2 FS. In this paper, a type-2 FS is proposed to remove variable gaussian noise from a...
Image in the process of collection and storage can produce noise. Wavelet threshold de-noising is a method to remove noise effectively. The threshold function is a key in wavelet threshold de-noising method. In view of the hard-threshold function discontinuity and soft-threshold function deviation problem, through the analysis of the existing wavelet threshold de-noising methods, we present the improvement...
The random noise is an important factor that affects the precision of MEMS gyroscope. Analyzed the noise characteristic of gyroscope by using Allan variance, introduced the thought of wavelet threshold de-noising method, and presented an improved wavelet threshold quantization function. Expatriate the complete build process of wavelet threshold denoising scheme and examined the effectiveness and repeatability...
In this article, the characteristics, theories and classification of the threshold de-noising method are introduced in detail. According to the study, when wavelet threshold de-noising method is compared with the wavelet packet threshold de-noising method, the first method is suitable for dealing with the low frequency information, but the second method is available to deal with the information with...
Aiming at solving the noise problem which had lowered the accuracy in the target detection result from the process of image-collection and image-transmission, the paper proposes a new target detection algorithm based on the improved wavelet threshold. Firstly, these images are filtered by a denoising method, which combines the wavelet threshold method with the correlation of the wavelet coefficients,...
Image de-noising is an important step to improve the AOI (automated optical inspection) image quality of automobile work piece. After analyzing the theory of wavelet transform and the characteristics of traditional soft and hard wavelet threshold de-noising methods, an improved threshold de-noising method was proposed. The new method overcomes the discontinuous in hard threshold de-noising method...
In this paper, a new adaptive multi-thretholding image denoising method based on the decomposition order is presented, which is built upon the ideas of Embedded Zero tree Wavelet (EZW) encoder and separate character of signals and noises. This method is not increase in operation amounts but excellent in image denoising results.
In the avionics test, sensor signal samplings are often subjected to the interference of all kinds of noise, which could not accurately reflect the real operating status of the equipment and should not be directly used for data processing and analysis. In order to de-noise test data, a new threshold function is presented and the preprocessing wavelet is determined by reconstruction factor according...
Existing de-noising algorithm's de-noising result is not satisfactory. In response to this phenomenon, this paper presents an improved soft threshold de-noising algorithm based on sensitive characteristics of the human visual. According to the inherent characteristics of the human eye's visual, we improved soft threshold de-noising algorithm. After simulation experiment, the experimental results conform...
In order to preserve fine details in image denoising, we propose a scheme by assuming that the deviations of the noisy and the original wavelet coefficients of image are not always the same across the scales. The proposed algorithm considers not only the correlation of inter-scale wavelet coefficients but also the mentioned assumptions. In the process of denoising, the proposed denoising threshold...
This paper deals with image denoising based on the wavelet transform realized by Mallat algorithm and À trous algorithm. The effectiveness of global and subband thresholding techniques are studied on multimedia and astronomical images contaminated by Gaussian noise. Experimental results on several testing images are compared with each other from two objective quality aspects (PSNR, RMSE). Astronomical...
Partial discharge (PD) is the initial sign of power capacitor insulation failure, and an effective extraction and analysis method of PD signal in power capacitor can improve the effectiveness of the on-line fault monitoring. The method which based on wavelet threshold denoising and mathematical morphology alternate mixing filter is put forward in this paper. First, the PD signal which includes noise...
Unmanned Aerial Vehicles (UAV) digital images are often badly degraded by noise during dynamic acquisition and transmission process. Denoising is very important and difficult for UAV-vision Guided, because natural scene image is complicated and having lots of the edges and texture details. The image denoising algorithm based on adaptive dual-tree discrete wavelet packets(ADDWP) which combine the dual-tree...
In fault detection of power system, the detection for mutations signal is very important. The application of wavelet coefficients correlation denoising in signal detection for noisy fault problem is relatively widespread. However, after doing wavelet transform to the noisy signal, the wavelet coefficients of each scale will produce a small offset. This paper presents a wavelet coefficients correlation...
This paper proved a new adaptive threshold in spherical coordinate system based on Besov space norm theory for application of the internet of things (IOT). It presented a new adaptive curve shrinkage function to overcome the limitation of translational functions. The new function could reach and exceed the true value and enhance the image edge. According to the image statistical characteristics in...
Image in the collection, transmission and other processes, often affected to some extent, resulting in noise. The purpose of image denoising is obtained from the degraded image noise removal, restore the original image. Traditional denoising methods can filter noise, but at the same time they make the image details fuzzy. The support vector machine based method for image denoising is a good method,thus...
The problem of reconstructing digital images from degraded measurement is regarded as a problem of importance in various fields of engineering and imaging sciences. The main goal of denoising is to restore a noisy image to produce visually high quality image. In general, image denoising imposes a compromise between noise reduction and preserving significant image details. In this paper we propose...
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