Lossy compression of images corrupted by film grain noise

Author

Al-Shaykh, Osama K. ; Mersereau, Russell M.

Author_Institution

Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

1

fYear

1996

fDate

16-19 Sep 1996

Firstpage

805

Abstract

Noise degrades the performance of any image compression algorithm. This paper studies the effect of film-grain noise on lossy image compression. Since the goal of lossy image compression algorithms is to achieve the best fidelity for a given bit rate, the distortion is measured with respect to the original image not with respect to the input to the coder. The results of noisy source coding are used to develop this coder. The minimum-mean-squared-error (MMSE) coder involves MMSE restoration of the noisy image. This paper presents an MMSE image restoration algorithm based on modeling the image as a Markov random field. The performance of this preprocessing step is also studied when using JPEG

Keywords

Markov processes; image coding; image restoration; least mean squares methods; noise; random processes; source coding; transform coding; JPEG; MMSE image restoration algorithm; MMSE restoration; Markov random field; coder; distortion; film grain noise; image compression algorithm; image corruption; images lossy compression; minimum-mean-squared-error coder; modeling; noisy source coding; performance; preprocessing step; Bit rate; Degradation; Image coding; Image restoration; Image storage; Noise figure; Noise level; PSNR; Quantization; Source coding;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1996. Proceedings., International Conference on

Conference_Location

Lausanne

Print_ISBN

0-7803-3259-8

Type

conf

DOI

10.1109/ICIP.1996.559621

Filename

559621