Earticle

초록

영어

Due to limited depth of field of machine vision cameras, multifocused image fusion is finding importance to produce a single image called fused image from various images of the same scene being imaged. To have focused images of all the objects in the scene, the fused image is formed by combining important features of various images. This in turn increases the importance of ability to assess the quality of the fused image more accurately. To be accurate, a typical image quality measure should be independent of image content, robust to noise, monotonic with respect to image blur and calculated with minimal computation complexity. In this paper, the performance of nine image quality measures were assessed through various experiments by applying image blur, adding image noise, changing image contrast and image saturation level. Experiments were also conducted on six sets of images to find the best image quality measure for multifocused image fusion.

목차

Abstract
 1. Introduction
 2. Image Quality Measures
 3. Evaluation of Image Quality Measures
  3.1. Sensitivity to Image Blurs
  3.2. Sensitivity to Image Noises
  3.3 Sensitivity to Image Contrast
  3.4 Sensitivity to Image Saturation
 4. Multifocused Image Fusion
 5. Conclusion
 References

키워드

저자

• K. Kannan [ Department of Mechatronics, Kamaraj College of Engineering and Technology, Virudhunagar – 626001, 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