Earticle

초록

영어

Histogram Equalization (HE) is a simple and effective image enhancement technique.But, it tends to change the mean brightness of the image to the middle level of the permitted range, and hence is not a very suitable for consumer product. While preserving the original brightness is essential to avoid annoying artefacts. To preserve brightness and to enhance contrast of images, numerous methods are introduced, but many of them present unwanted artefacts such as intensity saturation, over-enhancement and noise amplification. In the present paper, available histogram equalization based methods are reviewed and compared with image quality measurement (IQM)tools such as Absolute Mean Brightness Error (AMBE) to assess brightness preserving and Peak Signal-to-Noise Ratio (PSNR) to evaluate contrast enhancement.

목차

Abstract
 1. Introduction
  1.1. Histogram Equalization Methods
 2. Histogram Equalization based Techniques
  2.1. Bi-Histogram Equalization Methods
  2.2. Multi Histogram Equalization Methods
  2.3. Clipped Histogram Equalization Methods
 3. Image Quality Measurement Tools
  3.1 . Absolute Mean Brightness Error (AMBE)
  3.2. Peak Signal-to-Noise Ratio (PSNR)
 4. Results and Discussion
 5. Conclusions
 References

키워드

저자

• Raju. A [ Research Scholar ]
• Dwarakish. G. S [ Professor, Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal, India ]
• D. Venkat Reddy [ Professor, Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal, India ]

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