Skip to main navigation
Skip to search
Skip to main content
The UWS Academic Portal Home
Help & FAQ
Link opens in a new tab
Search content at The UWS Academic Portal
Home
Profiles
Research units
Research output
Activities
Press/Media
Projects
Prizes
Convolved feature vector based adaptive fuzzy filter for image de-noising
Muhammad Habib
, Ayyaz Hussain
, Eid Rehman
, Syeda Mariam Muzammal
, Benmao Cheng
, Muhammad Aslam
*
, Syeda Fizzah Jilani
*
Corresponding author for this work
Research output
:
Contribution to journal
›
Article
›
peer-review
13
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Convolved feature vector based adaptive fuzzy filter for image de-noising'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Image Denoising
100%
Feature Vector
100%
Adaptive Fuzzy Filter
100%
Vector-based
100%
Detail Preservation
50%
Stride Rate
50%
Noise Free
50%
Noisy pixel
50%
Noisy Image
25%
Filter Method
25%
Fuzzy Inference System
25%
Fuzzy Rules
25%
Performance Measures
25%
State-of-the-art Techniques
25%
Removal Efficiency
25%
Edge Information
25%
Detection Mechanism
25%
Hidden Patterns
25%
Existing State
25%
Fuzzy Membership Degree
25%
Vector Layer
25%
Weighted Kernel
25%
Information Pattern
25%
Degree Set
25%
Noise Detection
25%
Image pixels
25%
Fuzzy Filter
25%
Right Corners
25%
Input Layer
25%
Pixel-based
25%
Free Edge
25%
Noise Removal
25%
Impulse Noise Removal
25%
Reduced Set
25%
Engineering
Feature Vector
100%
Filtration
50%
Input Image
50%
Fuzzy Inference System
25%
Performance Measure ψ
25%
Fuzzy Rules
25%
Edge Information
25%
State-of-the-Art Technique
25%
Input Layer
25%
Impulse Noise
25%
Free Edge
25%
Membership Degree
25%
Noisy Image
25%
Fuzzy System
25%
Computer Science
image denoising
100%
Feature Vector
100%
Inference System
25%
Large Data Set
25%
Edge Information
25%
Detection Mechanism
25%
Performance Measure
25%
Membership Degree
25%
Top Left Corner
25%