Comparative Performance Evaluation of Three Image Compression Algorithms
The advent of computer and internet has brought about massive change to the ways images are being managed. This revolution has resulted in changes in image processing and management as well as the huge space requirement for images’ uploading, downloading, transferring and storing nowadays. In guidin...
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| Published in: | Journal of Applied Science & Process Engineering Vol. 4; no. 1; pp. 113 - 126 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
UNIMAS Publisher
28.04.2017
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| Subjects: | |
| ISSN: | 2289-7771, 2289-7771 |
| Online Access: | Get full text |
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| Summary: | The advent of computer and internet has brought about massive change to the ways images are being managed. This revolution has resulted in changes in image processing and management as well as the huge space requirement for images’ uploading, downloading, transferring and storing nowadays. In guiding against this huge space requirement, images need to be compressed before either storing or transmitting. Several algorithms or techniques on image compression had been developed in literature. In this study, three of these image compression algorithms were developed using MATLAB codes. The three algorithms developed are discrete cosine transform (DCT), discrete wavelet transform (DWT) and set partitioning in hierarchical tree (SPIHT). In order to ascertain which of them is most appropriate for image storing and transmission, comparative performance evaluations were conducted on the three developed algorithms using five performance indices. The results of the comparative performance evaluations show that the three algorithms are effective in image compression but with different efficiency rates. In addition, the comparative performance evaluations results show that DWT has the highest compression ratio and distortion level while the corresponding values for SPIHT is the lowest with those of DCT fall in-between. Also, the results of the study show that the lower the mean square error and the higher the peak signal-to-noise-ratio, the lower the distortion level in the compressed image. |
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| ISSN: | 2289-7771 2289-7771 |
| DOI: | 10.33736/jaspe.371.2017 |