Homogeneous Image Compression Techniques with the Shannon-Fano Algorithm
Abstract
Compression is a field that needed at this time where increasingly high-tech digital and computing makes it possible to process data in a size that is large enough like multimedia. Compression needed to keep pressing the storage media consumption of data and information stored on computer media. The Shannon-Fano compression algorithm is one of the well-known compression algorithms and is useful in saving data storage space. Shannon-Fano compression algorithms can be performed on text and digital images. In this study applying the Shannon-Fano method to homogeneous digital images using applications created with the MATLAB Program. The product of this research will be tested using several images taken using a webcam. The product tested to find out whether the coding used is correct or has errors. The product will be successful if it can reduce the size of the compressed image from the original image. Homogeneous images that have tested using the Shannon-Fano image compression application have an average compression ratio value of 52%. The size of the compression results reaches half of the original image. The Shannon-Fano compression algorithm detects the number of times that characters appear in each experiment, then the coding of the frequency of characters appearing in binary numbers.
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