Image denoising for reduced-search fractal block coding

Bal, Sandeep; Kinsner, W.

doi:10.1109/ccece.1996.548130

Cited by 1 publication

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Spatial filters have been used for a long time to remove noise from images and signals as the traditional way [41]. These filters reduce noise by means of smoothing data, however, they also cause a portion of signal loss from the signal itself (blur the data) [42]. The Savitzky-Golay smoothing filter, a famous member of the Spatial Smoothing filter family, has been implemented to evaluate the noise reduction effect for the noise corrupted optical signal in this study.…”

Section: Brief Introduction On Noise Reductionmentioning

confidence: 99%

Modeling and real-time feedback control of MEMS device

Wang¹

View full text Add to dashboard Cite

Modeling and Real-Time Feedback Control of MEMS Device Limin Wang Applying closed-loop control to a MEMS devices not only can handle the abnormal behaviors caused by manufactory imprecision or device failure, enabling MEMS devices to survive in critical conditions, but also can increase the application where MEMS devices are used to drive components under varying load conditions. This study mainly focuses on the effort of closed-loop control on the Lateral Comb Resonator (LCR) MEMS device. The success of closed-loop control has been achieved on lateral comb resonator with novel integrated through wafer optical monitoring technique [1]. Availability of a system model and feedback signals are mandatory conditions for the implementation of closed-loop control. Because of the fabrication process tolerance, the parameters of the Lateral Comb Resonator (LCR)'s model, especially the damping parameterβ, cannot be determined accurately based merely on theoretical analysis. Therefore, performing system identification through experiments can be a tool to verify the system model. Three different system identification methods in both the time domain and frequency domain have been implemented, and the results agree. Noise analysis on the optical monitoring signal shows that at least 90% of the noise in the signal is due to the optical monitoring setup, and the simulation shows that both a wavelet thresholding method and frequency domain low pass filter are efficient in removing this Gaussian distributed noise. Different designs are developed to monitor the LCR, both for single opening and grating structure LCRs, resulting in monitoring signals that are very different in nature. The optical monitoring signal for single opening device is highly correlated with the LCR's shuttle position. After removing the noise, this signal can be used directly as a feedback signal to perform closed-loop control on the shuttle for damping shock effect or to perform stroke-length control on the shuttle [2]. The optical monitoring signal for the grating structure LCR is a kind of frequency modulation of the shuttle's displacement. Based on this signal, both position and velocity signals can be reconstructed in real time [1,3]. Even though the reconstructed position and velocity signals will inherit and even amplify all the noises that exists in the optical monitoring signal, with this method acceptable performance has been achieved in the tracking control experiment of the LCR's shuttle. In this experiment, the newly designed model reference adaptive fuzzy sliding controller (MFSC) effectively minimized the side effects caused by either signal noise or imprecision of the system model. Furthermore, experimental success on force estimation has been achieved based on this signal reconstruction method [4]. The signal reconstruction method, which can decouple the noise from the optical signal, has been implemented. 2µm's resolution can be achieved with the current single beam optical monitoring method. The resolution can be improved several times with...

show abstract

Section: Brief Introduction On Noise Reductionmentioning

confidence: 99%

Modeling and real-time feedback control of MEMS device

Wang¹

View full text Add to dashboard Cite

show abstract

Image denoising for reduced-search fractal block coding

Cited by 1 publication

References 3 publications

Modeling and real-time feedback control of MEMS device

Modeling and real-time feedback control of MEMS device

Contact Info

Product

Resources

About