Title :
Bi-level image compression using adaptive tree model
Author :
Nguyen-Phi, Khanh ; Weinrichter, Hans
Author_Institution :
Wien Univ., Austria
Abstract :
Summary form only given. State-of-the-art methods for bi-level image compression rely on two processes of modelling and coding. The modelling process determines the context of the coded pixel based on its adjacent pixels and using the information of the context to predict the probability of the coded pixel being 0 or 1. The coding process will actually code the pixel based on the prediction. Because the source is finite, a bigger template (more adjacent pixels) doesn´t always lead to a better result, which is known as “context dilution” phenomenon. The authors present a new method called adaptive tree modelling for preventing the context dilution. They discussed this method by considering a pruned binary tree. They have implemented the proposed method in software
Keywords :
adaptive codes; image coding; source coding; tree data structures; adaptive tree model; adjacent pixels; bi-level image compression; coded pixel; coding process; context dilution; modelling process; prediction; pruned binary tree; template; Binary trees; Context modeling; Image coding; Predictive models; Testing; Tree data structures;
Conference_Titel :
Data Compression Conference, 1997. DCC '97. Proceedings
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-7761-9
DOI :
10.1109/DCC.1997.582122