EFFICIENCY ANALYSIS OF TETROLET TRANSFORM-BASED FILTERING BY REMOVAL OF ADDITIVE NOISE IN IMAGES

EFFICIENCY ANALYSIS OF TETROLET TRANSFORM-BASED FILTERING BY REMOVAL OF ADDITIVE NOISE IN IMAGES

Рубель, Андрей Сергеевич;Лукин, Владимир Васильевич;
Радіоелектронні і комп'ютерні системи 2017 pp. 4-20
190
2017efficiency

Abstract

Efficiency of filtering based on tetrolet transform for test image database with different properties distorted by additive white Gaussian noise with different intensity is investigated. As the performance criteria, both standard metrics, for instance, PSNR and visual quality metrics (PSNR-HVS-M, MSSIM, and FSIM) are used. Effect of test image features on optimal threshold is analyzed. A comparative analysis of the tetrolet transform-based filter with DCT-filter with respect toobject edge preservation and effective denoising is shown

Citation

ID: 85442
Ref Key: 2017efficiency
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
85442
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet