Earticle

초록

영어

The aim of image enhancement is to or to provide ‘better’ input for other improve the interpretability or perception of information in images for human viewing automated image processing techniques. Various Histogram Equalization techniques like CHE, GHE, BBHE, DSIHE, RMSHE and Multi-HE techniques are used for processing the image input to enhance its output. This paper provides a review over the modification of the brightness preserving dynamic histogram equalization technique to improve its brightness preserving and contrast enhancement abilities while reducing its computational complexity. There are many modified technique related to brightness preserving dynamic Histogram Equalization that uses statistics of digital images for their representation and processing are discussed here. Representation and processing of images in the spatial domain enables the technique to handle the inexactness of gray level values in a better way, resulting in improved performance. This algorithm enhances image contrast as well as preserves the brightness very effectively. Some images are not available to good quality, so these algorithms are used for image enhancement to improve the quality of the image.

목차

Abstract
 1. Introduction
 2. Image Enhancement by Histogram Equalization
 3. Extension to Histogram Equalization
 4. Brightness Preserving Techniques Application in Image Enhancement
 5. Fuzzy Statistics in Image Enhancement
 6. Image Enhancement Application in Real Time
 References

키워드

저자

• Mahendra PS Kuber [ Department of C.S.E. & I.T. Madhav Institute of Technology and Science, Gwalior, India ]
• Manish Dixit [ Department of C.S.E. & I.T. Madhav Institute of Technology and Science, Gwalior, 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