An Efficient Image Compression Using Enhanced Huffman Algorithm
Authors
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S. Agber
Department of Mathematics and Computer Science, Benue State University, Makurdi – Nigeria. email: seseagber@gmail.com
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I. Agaji
Department of Computer Science, Joseph Sarwuan Tarkar University, Makurdi – Nigeria. email: sasemiks@gmail.com
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B. O. Akumba
Department of Mathematics and Computer Science, Benue State University, Makurdi – Nigeria. email: beatriceakumba@gmail.com
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S. I. Odoh
Department of Computer Science, Federal University Lafia – Nigeria. email: odohisahsamuel@gmail.com
Abstract
Data compression involves removing redundant bits from the sourcern data, thereby reducing the total size of the data in a manner that allowsrn the process to be reversed when desired. For images, this involvesrn either removing redundant pixels or representing the pixels with arn smaller number of bits. The problem addressed in this paper is thern inefficiency of the traditional Huffman coding algorithm in compressingrn certain types of image files. To overcome this, we developed anrn enhanced algorithm by modifying the Huffman coding technique. Ourrn methodology includes designing the enhanced Huffman algorithm torn better handle image data by considering pixel distribution and frequencyrn more effectively. We implemented the modified algorithm and evaluatedrn its performance against the traditional Huffman algorithm using a varietyrn of image formats: BMP, JPG, PNG, TIF, and GIF. The performancern metrics used for evaluation were compression ratio and compressionrn time. The results show that the Modified Huffman algorithm achievesrn superior compression ratios for BMP, JPG, PNG, and TIF images, withrn quantitative improvements of 0.91, 0.90, 0.91, 0.80 respectively,rn compared to the traditional Huffman algorithm. However, for GIFrn images, the traditional Huffman algorithm demonstrated a higherrn compression ratio by 0.64. These results indicate that the Modifiedrn Huffman algorithm provides a more efficient solution for compressingrn most image formats, except for GIF images where the traditionalrn method remains preferable. This enhanced algorithm can be highlyrn beneficial for applications requiring optimized image storage andrn transmission.
Keywords: Data compression, Image compression, Huffman coding, Compression ratio