Jove
Visualize
Contact Us

Related Experiment Videos

Histogram-based fuzzy filter for image restoration.

Jung-Hua Wang1, Wen-Jeng Liu, Lian-Da Lin

  • 1Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|February 2, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Full-Scale Aggregated MobileUNet: An Improved U-Net Architecture for SAR Oil Spill Detection.

Sensors (Basel, Switzerland)·2024
Same author

Anomalous behavior recognition of underwater creatures using lite 3D full-convolution network.

Scientific reports·2023
Same author

Bio-inspired contour extraction via EM-driven deformable and rotatable directivity-probing mask.

Scientific reports·2022
Same author

Underwater Image Enhancement Based on Histogram-Equalization Approximation Using Physics-Based Dichromatic Modeling.

Sensors (Basel, Switzerland)·2022
Same author

Identification of Genes Related to Cold Tolerance and Novel Genetic Markers for Molecular Breeding in Taiwan Tilapia (<i>Oreochromis</i> spp.) via Transcriptome Analysis.

Animals : an open access journal from MDPI·2021
Same author

Bayesian Edge Detector Using Deformable Directivity-Aware Sampling Window.

Entropy (Basel, Switzerland)·2020
Same journal

Strategic Ability Updating in Concurrent Games by Coalitional Commitment.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2015
Same journal

Meta-Analysis of the First Facial Expression Recognition Challenge.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012
Same journal

Adjustable model-based fusion method for multispectral and panchromatic images.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012
Same journal

Face Feature Weighted Fusion Based on Fuzzy Membership Degree for Video Face Recognition.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012
Same journal

A New Adaptive Fast Cellular Automaton Neighborhood Detection and Rule Identification Algorithm.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012
Same journal

Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2012
See all related articles
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

This study introduces a novel fuzzy smoothing filter for effective impulsive noise removal in images. The filter preserves image details and outperforms traditional methods without requiring training.

Area of Science:

  • Image Processing
  • Computer Vision
  • Artificial Intelligence

Background:

  • Image noise corruption, particularly impulsive noise, degrades image quality and hinders analysis.
  • Conventional filters like Median Filters (MF) have limitations in effectively removing high levels of impulsive noise while preserving fine image details.

Purpose of the Study:

  • To present a novel fuzzy smoothing filter for robust restoration of noise-corrupted images.
  • To demonstrate the filter's effectiveness in removing highly impulsive noise while preserving essential image details.
  • To achieve superior performance compared to existing filters without requiring extensive training.

Main Methods:

  • A fuzzy smoothing filter is developed using fuzzy membership functions.
  • Initial filter parameters are derived from the input image histogram.

Related Experiment Videos

  • Histogram potential conservation principles and input statistics are used to optimize parameters, minimizing defuzzification discrepancies.

    • Main Results:

    • The proposed filter effectively removes highly impulsive noise.
    • Image details are well-preserved during the noise restoration process.
    • Performance is superior to conventional filters, including MF, across various impulsive noise probabilities.

    Conclusions:

    • The novel fuzzy smoothing filter offers an effective and efficient solution for impulsive noise reduction.
    • The filter's parameter derivation method eliminates the need for training, making it practical for diverse applications.
    • This approach provides a significant advancement in image restoration techniques.