Earticle

초록

영어

New innovative research trends are more essential in the area of image compression for various imaging applications. These applications require good visual quality in processing. In general the tradeoff between compression efficiency and picture quality is the most important parameter to validate the work. The existing algorithms for still image compression were developed by considering the compression efficiency parameter by giving least importance to the visual quality in processing. Hence, we proposed a novel lossless image compression algorithm which efficiently suited for various types of digital images. Thus, in this work, we specifically address the following problem that is to maintain the compression ratio for better visual quality in the reconstruction and considerable gain in the values of Peak Signal to Noise Ratio (PSNR). We considered medical images , satellite extracted images and natural images for the inspection and proposed a novel procedure named as Novel Optimized Golomb Rice Coding (NOGR) to increase the visual quality of the reconstructed image. The result of the proposed technique outperforms present techniques and the results are simulated using MATLAB.

목차

Abstract
 1. Introduction
 2. Literature Survey
 3. Brief Note on Golomb-Rice Coding
 4. The Concept of Proposed Optimized Technique
 5. Flow Chart of NOGR Coding
 6. Scalar Quantization
 7. NOGR Coding Procedure
 8. Simulation Results
 9. Conclusion
 Acknowledgements
 References

키워드

저자

• Shaik Mahaboob Basha [ Research Scholar, Department of E.C.E., J.N.T.University, Hyderabad, A.P., India ]
• B. C. Jinaga [ Professor in E.C.E (Retd), Department of E.C.E, J.N.T.University, Hyderabad, A.P., 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