Finite state DCT with global bitmap image coding

Yung Gi Wu, Shen Chuan Tai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The ordinary DCT coding techniques always classify the image into 4 classes, then select suitable bitmaps for the 4 classes. This is not enough for complicated images. In order to encode the image in more detail, the authors classify the image into 16 classes. This classification can reduce the artifacts which are caused by the ordinary coding scheme. However, it will take a lot of time to generate the 16 bitmaps for the 16-class classification. Besides, it will take a very large overhead to transmit the 16 bitmaps. In order to solve the deficiency, the authors developed the concept of global bitmaps of 16 classes which can be used for all the images. As to the side information of the classification, the authors use the idea of the finite state machine to predict the current class from the previously classes. Thus, the overhead of the class will be reduced. The experimental results show that the performance of the coding system is very good and the prediction correct ratio can be over 70% in the Lena image.

Original languageEnglish
Title of host publicationISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages193-196
Number of pages4
ISBN (Electronic)078031865X, 9780780318656
DOIs
Publication statusPublished - 1994 Jan 1
Event1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994 - Hong Kong, Hong Kong
Duration: 1994 Apr 131994 Apr 16

Publication series

NameISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings

Conference

Conference1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994
CountryHong Kong
CityHong Kong
Period94-04-1394-04-16

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Linguistics and Language

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