Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Fixation and Sectioning01:03

Fixation and Sectioning

Two basic types of preparation are used to visualize specimens with a light microscope: wet mounts and fixed specimens.
The simplest type of preparation is the wet mount, in which the specimen is placed in a drop of liquid on the slide. A liquid specimen can be directly deposited on the slide using a dropper. Solid specimens, such as skin scraping, can be placed on the slide before adding a drop of liquid to prepare the wet mount. Sometimes the liquid is simply water, but stains are often added...
Deconvolution01:20

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...
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...
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Fischer Projections02:18

Fischer Projections

Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...

You might also read

Related Articles

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

Sort by
Same author

Whole-genome resequencing reveals the genetic diversity, population structure and selection signatures in Chinese indigenous Kele pigs.

Frontiers in veterinary science·2025
Same author

Perceptually-Guided VR Style Transfer.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

In Vitro Analysis of LPS-Induced miRNA Differences in Bovine Endometrial Cells and Study of Related Pathways.

Animals : an open access journal from MDPI·2024
Same author

Rational design of nanoscale stabilized oxide catalysts for OER with OC22.

Nanoscale·2024
Same author

3D-PSSIM: Projective Structural Similarity for 3D Mesh Quality Assessment Robust to Topological Irregularities.

IEEE transactions on pattern analysis and machine intelligence·2024
Same author

Nitrogen doped small molecular structures of nano-graphene for high-performance anodes suitable for lithium ion storage.

RSC advances·2022

Related Experiment Videos

Foveation scalable video coding with automatic fixation selection.

Zhou Wang1, Ligang Lu, Alan Conrad Bovik

  • 1Lab. for Image and Video Eng., Univ. of Texas, Austin, TX 78712, USA. zhouwang@ieee.org

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a foveation scalable video coding (FSVC) algorithm. It enhances video quality and compression by integrating human visual system (HVS) models for rate scalability.

Related Experiment Videos

Area of Science:

  • Computer Vision
  • Signal Processing
  • Multimedia Systems

Background:

  • Image and video coding is an optimization challenge balancing quality and performance.
  • Current research trends include Human Visual System (HVS) integration and rate scalability.

Purpose of the Study:

  • To propose a foveation scalable video coding (FSVC) algorithm.
  • To achieve high quality-compression performance and effective rate scalability.

Main Methods:

  • Incorporating a foveation-based Human Visual System (HVS) model.
  • Organizing the encoded bitstream for optimal decoded video at varying bit rates.
  • Developing a rate scalable video codec.

Main Results:

  • The proposed FSVC algorithm demonstrates good quality-compression performance.
  • Effective rate scalability is achieved, allowing continuous bit rate extraction.
  • The algorithm leverages foveated visual quality measurement.

Conclusions:

  • The FSVC algorithm successfully integrates HVS models for improved video coding.
  • The approach offers adaptability for diverse applications like knowledge-based coding and network communications.
  • This method provides a novel solution for rate scalable video compression.