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Related Concept Videos

Upsampling01:22

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...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...
Downsampling01:20

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...
Stereoisomers02:32

Stereoisomers

On the basis of mirror symmetry, stereoisomers of an organic molecule can be further classified into diastereomers and enantiomers. Diastereomers are stereoisomers that are not mirror images of each other. Substituted alkenes, such as the cis and trans isomers of 2-butene, are diastereomers, as these molecules exhibit different spatial orientations of their constituent atoms, are not mirror images of each other, and do not interconvert. Here, the interconversion is suppressed due to restricted...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...

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Direct Linear Transformation for the Measurement of In-Situ Peripheral Nerve Strain During Stretching
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A least-squares-based 2-D filtering scheme for stereo image compression.

S H Seo, M R Azimi-Sadjadi, B Tian

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |February 12, 2008
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel 2-D least squares (LS) filtering method for high-fidelity stereo image compression. The technique effectively reduces mismatching errors in stereo pairs, improving 3D-TV applications.

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    Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

    Published on: June 2, 2010

    Area of Science:

    • Digital Image Processing
    • Computer Vision
    • Signal Processing

    Background:

    • Stereo image compression is crucial for high-fidelity 3D-TV applications.
    • Mismatching effects in stereo image pairs degrade compression quality.
    • Existing block-matching methods can be computationally intensive and prone to errors.

    Discussion:

    • A novel two-dimensional (2-D) least squares (LS)-based filtering scheme is proposed for stereo image compression.
    • The method utilizes the left image as a reference input and the right image as the desired output for a 2-D transversal filter.
    • Filter weights are determined using a block-based LS approach, with a reduced-order scheme optimizing filter coefficients.

    Key Insights:

    • The proposed LS-based filtering effectively removes mismatching effects in stereo image pairs.
    • Reconstruction of the right image at the receiver uses principal coefficients and disparity vectors with the left image.
    • Performance was evaluated on a real stereo image pair for 3D-TV, showing competitive results against block-matching methods.

    Outlook:

    • Further research could explore adaptive filtering schemes for varying stereo image content.
    • Optimization of the reduced-order filtering for real-time 3D-TV applications is a potential future direction.
    • Integration of this LS-based approach with other compression techniques could yield enhanced performance.