Earticle

초록

영어

In advanced image processing, aerial image processing plays an important role in object extraction such as building extraction, road detection etc. The aerial images captured are usually bound to suffer from Gaussian noise, salt and pepper noise, speckle noise etc. Therefore obtaining of aerial image with high accuracy is very difficult task. A flawless aerial image is inevitable for further object extraction process. There are a number of filtering techniques to detach the noise for preserving the integrity of captured aerial image. In this paper we have applied mean filter, median filter, wiener filter, wavelet transform and curvelet transform for removal of various level of Gaussian noise, salt and pepper noise and speckle noise added separately in an aerial image. The performance of both the transforms and filtering methods are compared in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE).

목차

Abstract
 1. Introduction
 2. Types of Noise
  2.1. Gaussian Noise
  2.2. Salt and Pepper Noise
  2.3. Speckle Noise
 3. Some Existing Filtering Techniques
  3.1. Mean Filter
  3.2. Median Filter
  3.3. Wiener Filter
  3.4. Wavelet Transform
  3.5. Curvelet Transform
 4. Comparative Study
 5. Conclusion
 References

키워드

저자

• Sheikh Tania [ Bangladesh University of Engineering and Technology ]
• Raghad Rowaida [ Bangladesh University of Engineering and Technology ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605