Abstract
ABSTRACTThe maps and images of geographical information system (GIS) are used for finding locations, accessing rail, bus routes, and for educational purposes such as study on vegetation, landscapes, population, and so on and so forth. Remote sensing is the process of acquiring data about Earth by using satellites or satellite-borne or airborne sensors. The images acquired through remote sensing systems are integrated within GIS to store, analyze, and manipulate geographical information of the Earth. The huge size of the digital raster maps makes compression inevitable in particular to reduce the transmission time and display them on the Internet as well as other networks. In this paper, a lossless coding approach that performs encoding on the decomposed binary layers by taking the advantage of binary wavelet transform that produces sparse matrix for row column reduction and Huffman coding is presented. The results obtained on raster maps are compared with those of other existing techniques.
Highlights
A lossless coding approach that performs encoding on the decomposed binary layers by taking the advantage of binary wavelet transform that produces sparse matrix for row column reduction and Huffman coding is presented
Images obtained from satellites and other airborne imaging systems are often referred as remote sensing data (Liu and Mason 2009)
The United States Geological Survey (USGS), a civilian federal agency, produces several national series of topographic maps which vary in scale and extent
Summary
Images obtained from satellites and other airborne imaging systems are often referred as remote sensing data (Liu and Mason 2009). Topographic maps are created using photogrammetric interpretation of various images obtained from satellites, LiDAR, or other remote sensing systems These maps comprise various layers such as roads, forest cover, urban areas, contours, streams, lakes, etc. Raster files are in particular used for storing remote sensing data These are used to store image information like scanned paper maps and aerial pictures. Raster data can be images with each pixel containing a color value and are stored in various formats, such as standard file-based structures (like TIF, JPEG, or Binary Large Object (BLOB) data). Based on the USGS standards, the color palette is limited to 13 colors to represent various areas such as road, water bases, vegetation, boundaries, contours, and revised areas This limitation in colors has advantage in compression due to the large size of the maps. Since the image is already sparse to certain extent due to decomposition, the 8 × 8 block undergoes RC reduction which reduces the block else a BWT that can produce sparse block is done followed by Huffman coding
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