BINARY IMAGE COMPRESSION USING NEIGHBORHOOD CODING Tiago B. A. de Carvalho1, Tsang Ing Ren1, George D.C. Cavalcanti1, Tsang Ing Jyh2 1Center of Informatics, Federal University of Pernambuco, Brazil. 2Alcatel-Lucent, Bell Labs, Belgium E-mail: 1{tbac,tir,gdcc}@cin.ufpe.br,
[email protected] ABSTRACT Bitmap image format requires a reasonable great amount of computer memory, since for each pixel it is necessary a Compression plays an important role in the storage and set of bits to represent it, and a relatively small image can transmission of digital image. Binary image compression is contain millions of pixels. Even a binary image that uses just of essential value for document imaging. Here, we propose a a bit per pixel can demand a large amount of disk space. novel compression technique based on the concept of There are dozens of bitmap image formats that use neighborhood coding, which codes each pixel of an image compression techniques, e.g., TIFF, GIF, PNG, JBIG and according to the number of neighbor pixels in different JPEG. The TIFF format can also use different types of directions. The proposed technique is a lossless compression compression methods such as CCITT Group 3 or Group 4. scheme, which also uses run-length encoding (RLE) and We propose a novel lossless binary image compression Huffman coding. We evaluated and compared this method to technique based on neighborhood coding scheme described several image file format, using test images taken from the in [2]. The codification starts by transforming each pixel of MPEG-7 core experiment CE-shape and the binary image the image into a vector.