Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Downsampling

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...

Upsampling

Upsampling

Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...

Deconvolution

Deconvolution

Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...

Design Example: Capacitance Multiplier Circuit

Design Example: Capacitance Multiplier Circuit

In integrated circuit technology, a capacitance multiplier is often utilized to produce a larger capacitance value when a small physical capacitance falls short. This is achieved by a circuit that multiplies capacitance values by a factor of up to 1000, such that a 10-pF capacitor can replicate the performance of a 100-nF capacitor.
The circuit illustrated in Figure 1 below incorporates two op-amps, with the first operating as a voltage follower and the second acting as an inverting amplifier.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Adaptive defect and pattern detection in amplitude and phase structures via photorefractive four-wave mixing.

Applied optics·2015

Same author

2.32 THz quantum cascade laser frequency-locked to the harmonic of a microwave synthesizer source.

Optics express·2012

Same author

Terahertz inverse synthetic aperture radar (ISAR) imaging with a quantum cascade laser transmitter.

Optics express·2010

Same author

Frequency stabilization of a single mode terahertz quantum cascade laser to the kilohertz level.

Optics express·2009

Same author

MEMS-based optical limiter.

Applied optics·2008

Same author

Terahertz sideband-tuned quantum cascade laser radiation.

Optics express·2008

Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026

Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026

Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026

Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026

Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026

Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 22, 2026

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Optical-limiter MEMS dynamic range compression deconvolution.

Bahareh Haji-saeed¹, William D Goodhue, Charles L Woods

¹Air Force Research Laboratory, Sensors Directorate, Hanscom Air Force Base, Massachusetts 01731, USA. bahareh.haji-saeed@hanscom.af.mil

|July 3, 2009

Summary

This summary is machine-generated.

We developed a new nonlinear optical-limiter microelectromechanical system (NOLMEMS) device for dynamic range compression deconvolution. This novel system effectively restores blurred images using nonlinear optical processing and spatial light modulation.

More Related Videos

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Published on: July 5, 2016

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

Related Experiment Videos

Last Updated: Jun 22, 2026

Lensless Fluorescent Microscopy on a Chip

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Published on: July 5, 2016

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

Published on: February 4, 2018

Area of Science:

Optics and Photonics
Microelectromechanical Systems (MEMS)
Image Processing

Background:

Image deconvolution is crucial for restoring clarity in blurred optical systems.
Traditional deconvolution methods often struggle with dynamic range limitations.
Microelectromechanical systems offer novel solutions for optical signal processing.

Purpose of the Study:

To introduce a novel nonlinear optical-limiter microelectromechanical system (NOLMEMS) device.
To demonstrate dynamic range compression deconvolution using the proposed NOLMEMS device.
To analyze the nonlinear transfer function and deconvolution capabilities of the NOLMEMS.

Main Methods:

Utilizing aperturized, reflected coherent light from optically addressed, deformable mirrors.
Employing a spatial light modulator (SLM) to process joint image and blur response information.
Applying Fourier transforms and nonlinear optical limiting for image restoration.

Main Results:

The NOLMEMS device exhibits a saturating nonlinear transfer function.
Computer simulations confirm the effectiveness of the NOLMEMS for image deconvolution.
The system successfully performs dynamic range compression during deconvolution.

Conclusions:

The proposed NOLMEMS device provides an effective method for dynamic range compression deconvolution.
This approach offers a new pathway for advanced optical image restoration.
Further research can explore the optimization and application of NOLMEMS in various imaging scenarios.