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Linear regression models for DCT domain approximate filtering and deblurring

  • Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper presents two linear regression models by exploring the relationships between DCT coefficients of the original image and filtered image. The first model is to scale the DCT coefficients of the original image in order to approximate the operation of 2-D spatial domain filtering. The second model is to predict the original image from the filtered image in a similar manner. We show that the first model is used for DCT domain filtering, while the second model can be used for fast DCT domain image deblurring. Both of them are easy to implement on compressed formats of DCT-based compression methods (JPEG, MPEG, H.26X) by using decoding quantization tables that are different from the encoding quantization tables.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings
Pages805-808
Number of pages4
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Hannover, Germany
Duration: 23 Jun 2008 → 26 Jun 2008

Publication series

Name2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings

Conference

Conference2008 IEEE International Conference on Multimedia and Expo, ICME 2008
Country/TerritoryGermany
CityHannover
Period23/06/08 → 26/06/08

Keywords

  • DCT-domain processing
  • Filtering
  • Quantization tables

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