Coupling denoising algorithm based on discrete wavelet transform and modified median filter for medical image

Chen, Bingquan; Cui, Jin-ge; Xu, Qing; Shu, Ting; Liu, Hongli

doi:10.1007/s11771-019-3987-9

Cited by 36 publications

(14 citation statements)

References 10 publications

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“…De-noising on the vehicle vibration data is required before the subsequent signal analysis since it is non-stationary signal contaminated with noise. Wavelet analysis can eliminate high-frequency noise while retaining useful high-frequency signals [17]. In this article, the signal is processed by the wavelet soft threshold de-noising method, which has been widely used in engineering.…”

Section: Signal De-noisingmentioning

confidence: 99%

Application of signal processing and support vector machine to transverse cracking detection in asphalt pavement

Yang

Zhou

Wang

et al. 2021

J. Cent. South Univ.

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Vibration-based pavement condition (roughness and obvious anomalies) monitoring has been expanding in road engineering. However, the indistinctive transverse cracking has hardly been considered. Therefore, a vehicle-based novel method is proposed for detecting the transverse cracking through signal processing techniques and support vector machine (SVM). The vibration signals of the car traveling on the transverse-cracked and the crack-free sections were subjected to signal processing in time domain, frequency domain and wavelet domain, aiming to find indices that can discriminate vibration signal between the cracked and uncracked section. These indices were used to form 8 SVM models. The model with the highest accuracy and F1-measure was preferred, consisting of features including vehicle speed, range, relative standard deviation, maximum Fourier coefficient, and wavelet coefficient. Therefore, a crack and crack-free classifier was developed. Then its feasibility was investigated by 2292 pavement sections. The detection accuracy and F1-measure are 97.25% and 85.25%, respectively. The cracking detection approach proposed in this paper and the smartphone-based detection method for IRI and other distress may form a comprehensive pavement condition survey system.

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Section: Signal De-noisingmentioning

confidence: 99%

Application of signal processing and support vector machine to transverse cracking detection in asphalt pavement

Yang

Zhou

Wang

et al. 2021

J. Cent. South Univ.

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“…However, there are cases when there is no improvement in contours. The quality of contours is especially important in the perception of images by the human visual system [43], so obtaining with the reduction of noise and an improvement in terms of contours and textures is an important goal in image processing.…”

Section: Multiple Wiener Filter In Wavelet Domainmentioning

confidence: 99%

Methods for Improving Image Quality for Contour and Textures Analysis Using New Wavelet Methods

2021

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The fidelity of an image subjected to digital processing, such as a contour/texture highlighting process or a noise reduction algorithm, can be evaluated based on two types of criteria: objective and subjective, sometimes the two types of criteria being considered together. Subjective criteria are the best tool for evaluating an image when the image obtained at the end of the processing is interpreted by man. The objective criteria are based on the difference, pixel by pixel, between the original and the reconstructed image and ensure a good approximation of the image quality perceived by a human observer. There is also the possibility that in evaluating the fidelity of a remade (reconstructed) image, the pixel-by-pixel differences will be weighted according to the sensitivity of the human visual system. The problem of improving medical images is particularly important in assisted diagnosis, with the aim of providing physicians with information as useful as possible in diagnosing diseases. Given that this information must be available in real time, we proposed a solution for reconstructing the contours in the images that uses a modified Wiener filter in the wavelet domain and a nonlinear cellular network and that is useful both to improve the contrast of its contours and to eliminate noise. In addition to the need to improve imaging, medical applications also need these applications to run in real time, and this need has been the basis for the design of the method described below, based on the modified Wiener filter and nonlinear cellular networks.

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“…Feature selection in an emotion recognition system is a NP-hard problem. e goal of establishing a good two-class emotion recognition system is to find a subset of initial features, which can minimize the loss rate and error rate of the system [9]. In the era of We Media, the new characteristics of social thoughts, the characteristics of college students themselves, the negative influence of society, and the poor effect of ideological and political education have impacted the socialist core values and affected the rational cognition, emotional identity, and practice of college students [10].…”

Section: Introductionmentioning

confidence: 99%

Research on Emotion Recognition and Mental State Prediction of College Students Based on Deep Neural Network

Qi¹,

Yang

2022

Mobile Information Systems

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Since entering the new century, people’s living standards have steadily improved, and their living conditions have also continuously improved. The improvement in living standards has brought greater pressure to people. The recognition of emotion and psychological state has become one of the research hotspots. Because of excessive work pressure, many students now suffer from depression. In this paper, we use a large number of research data and comparative charts to facilitate the analysis of the collected data. At the same time, we use LDA topic classification and NLDA neural network algorithm for refining and concise data processing. The research shows that students’ psychological state will affect their academic achievements. Students should try their best to manage their mental state, learn to know their emotional state, and ensure a good mental state. Emotional leadership is very important for students’ physical and mental health. Emotional leadership is a very important task for students and schools. Schools and students should actively cooperate to improve ’students’ ability to manage emotions, especially their ability to self-regulate emotions, and to jointly help build a harmonious campus. Because of the contradiction between the complexity of interpersonal relationship and society and the simplicity of students, students are often frustrated in interpersonal communication. The biggest reason for students’ psychological state is that they have no courage to express themselves in public, cannot communicate with others, and are interested in and concerned about the failure of various activities.

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Coupling denoising algorithm based on discrete wavelet transform and modified median filter for medical image

Cited by 36 publications

References 10 publications

Application of signal processing and support vector machine to transverse cracking detection in asphalt pavement

Application of signal processing and support vector machine to transverse cracking detection in asphalt pavement

Methods for Improving Image Quality for Contour and Textures Analysis Using New Wavelet Methods

Research on Emotion Recognition and Mental State Prediction of College Students Based on Deep Neural Network

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