Image analysis for adaptive noise reduction in super high-definition image coding

V. Ralph Algazi; Todd Randall Reed; Gary E. Ford; Robert R. Estes Jr.; Ashar Najmi

doi:10.1117/12.131492

1 November 1992 Image analysis for adaptive noise reduction in super high-definition image coding

V. Ralph Algazi, Todd Randall Reed, Gary E. Ford, Robert R. Estes Jr., Ashar Najmi

Proceedings Volume 1818, Visual Communications and Image Processing '92; (1992) https://doi.org/10.1117/12.131492
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

The encoding of Super High Definition Images presents new problems with regard to the effect of noise on the quality of images and on coding performance. Although the information content of images decreases with increasing resolution, the noise introduced in the image acquisition or scanning process, remains at a high level, independently of resolution. Although this noise may not be perceptible in the original image, it will effect the quality of the encoded image, if the encoding process introduces correlation and structure in the coded noise. Further, the coder performance will be affected by the noise, even if the noise is not perceived. Therefore, there is a need to reduce the noise by pre-processing the SHD image, so as to maintain image quality and improve the encoding process. The reduction of noise cannot be performed by low pass filtering operations that will degrade image quality. We are applying to this problem image analysis for adaptive noise removal. We discuss first the information theoretic issues on the effect of noise on coders. We then consider adaptive noise removal techniques to the perceptually transparent and very high quality coding of still SHD images.

Citation Download Citation

V. Ralph Algazi, Todd Randall Reed, Gary E. Ford, Robert R. Estes Jr., and Ashar Najmi "Image analysis for adaptive noise reduction in super high-definition image coding", Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); https://doi.org/10.1117/12.131492

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