Earticle

초록

영어

The main problem faced during biomedical image diagnosis is the noise introduced due to the consequence of the coherent nature of the image. The noise interfered may be Gaussian noise, speckle noise or Poisson noise, during transmission. The capturing devices itself has a salt & pepper noise. These noises corrupt the image and often lead to incorrect diagnosis. These noises make it more difficult for the observer to discriminate fine detail of the images in diagnostic examinations. Thus, denoising these noises from a noisy image has become the most important step in medical image processing. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. Denoising techniques are aimed at removing noise or distortion from images while retaining the original quality of the image. In this work, we propose PCA_NLM approach which computes neighborhood similarities after PCA projection. Our algorithm is based on the assumption that image contains an extensive amount of self-similarity. The accuracy and computational cost of the PCA algorithm is improved by computing neighborhood similarities, i.e., averaging weights, after a PCA projection to a lower dimensional subspace. We evaluate and compare the performance of proposed technique with different existing methods by using six quality measures PSNR, SNR, MSE, NAE, Correlation Coefficient and SSIM. Comparative analysis shows our approach give the best performance results in terms of improved quality measures as well as visual interpretation.

목차

Abstract
 1. Introduction
  1.1 Biomedical Imaging
 2. Concepts and Theory of Problem
 3. Results and Discussion
 4. Conclusions & Future Scope
 References

키워드

저자

• Mohit Bansal [ Assistant Professor, Department of Electronics and Communication Engineering GIET, Sonepat-131001, India ]
• Munesh Devi [ M.Tech. Scholar, Department of Computer Science Engineering SGI, Samalka -131001, India ]
• Neha Jain [ M.Tech. Scholar, Department of Electronics and Communication Engineering BMIET, Sonepat-131001, India ]
• Chinu Kukreja [ M.Tech. Scholar, Department of Computer Science Engineering SGI, Samalka -131001, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605