Title :
Lossless Compression of Maps, Charts, and Graphs via Color Separation
Author :
AlZahir, Saif ; Borici, Arber
Author_Institution :
Graphics & Image Process. Lab., Univ. of N. British Columbia, BC, Canada
Abstract :
Summary form only given. In this research, we present a fast and efficient lossless compression scheme for discrete-color digital map images, charts, and graphs stored in the raster image format. The proposed scheme determines the number of different colors in the given image and creates a separate bi-level data layer for each color. Then, the bi-level layers are individually compressed using the proposed algorithm. This scheme comprises two components: (i) a codebook; and (ii) our row-column reduction coding algorithm, RCRC. The codebook is a fixed-to-variable Huffman dictionary that is based on symbol entropy. The second component of our scheme is a new algorithm, the RCRC, designed to deal with those blocks that are not found in the codebook. Our experimental results show that our lossless compression scheme achieved an average compression equal to 0.035 bpp for map images and 0.03 bpp for charts and graphs. These results are better than most reported results in the literature. Moreover, our scheme is simple and fast.
Keywords :
Huffman codes; charts; data compression; entropy codes; graphs; image coding; image colour analysis; RCRC; bi-level data layer; charts; codebook; color separation; discrete-color digital map images; fixed-to-variable Huffman dictionary; graphs; lossless compression scheme; raster image format; row-column reduction coding algorithm; symbol entropy; Color; Computer graphics; Computer science; Data compression; Dictionaries; Entropy; Frequency; Image coding; Image processing; Partitioning algorithms;
Conference_Titel :
Data Compression Conference (DCC), 2010
Conference_Location :
Snowbird, UT
Print_ISBN :
978-1-4244-6425-8
Electronic_ISBN :
1068-0314
DOI :
10.1109/DCC.2010.102