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Convolution: Math, Graphics, and Discrete Signals01:24

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In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
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The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
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Convolution Properties I01:20

Convolution Properties I

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Convolution computations can be simplified by utilizing their inherent properties.
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Deconvolution01:20

Deconvolution

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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.
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Imaging Biological Samples with Optical Microscopy01:18

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Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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Related Experiment Video

Updated: Mar 31, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

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Group multiple-image encoding and watermarking using coupled logistic maps and gyrator wavelet transform.

Muhammad Rafiq Abuturab

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |October 20, 2015
    PubMed
    Summary
    This summary is machine-generated.

    A new method securely encodes and watermarks multiple images using coupled logistic maps and gyrator wavelet transform. This approach enhances security by embedding encrypted images within a host image, offering robust protection.

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    Area of Science:

    • Image processing
    • Cryptography
    • Wavelet transform

    Background:

    • Digital image security is crucial.
    • Existing methods face challenges in robustness and security.
    • Need for advanced encryption and watermarking techniques.

    Purpose of the Study:

    • To introduce a novel method for group multiple-image encoding and watermarking.
    • To enhance security and robustness of digital images.
    • To leverage chaotic systems and wavelet transforms for image protection.

    Main Methods:

    • Utilizes coupled logistic maps for chaotic permutation and gyrator wavelet transform for encoding.
    • Segregates images into R, G, B channels, permutes, and transforms them.
    • Embeds encrypted image phase information into host image subbands (HL, LH, HH) using discrete wavelet transform.

    Main Results:

    • Successfully encoded and watermarked multiple image groups with high security.
    • Demonstrated robustness against unauthorized access through large key space and dual protection (encryption + host image).
    • Numerical simulations confirmed the validity and security of the proposed scheme.

    Conclusions:

    • The proposed method offers a secure and robust solution for multiple-image encoding and watermarking.
    • The combination of chaotic maps and wavelet transforms provides a powerful tool for digital image protection.
    • The system's design allows for potential optoelectronic decryption, indicating practical applicability.