A Comparison of Some of the Most Current Methods of Image Compression
Robert T. Kay
Abstract
Open-access reader
Robert T. Kay
Abstract
Open-access reader
In this report, commonly used lossless and lossy image compression algorithms are heuristically presented and then compared in terms of performance. The lossy algorithms, JPEG (Joint Photographic Experts Group) and Fractal compression, are compared in terms of their respective sensitivities between compression ratio and image fidelity. Compression algorithms based on the lossless models of Huffman, Adaptive Huffman, and Arithmetic coding are compared in terms of compression ratio and compression/decompression time requirements. High fidelity image reconstructions of JPEG and Fractal compressions are also included in the comparison. Results, for the images tested, indicate that if imperceptible losses in fidelity can be tolerated, then among the current versions of the algorithms tested, the JPEG results in higher compression with less process time.
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In this report, commonly used lossless and lossy image compression algorithms are heuristically presented and then compared in terms of performance. The lossy algorithms, JPEG (Joint Photographic Experts Group) and Fractal compression, are compared in terms of their respective sensitivities between compression ratio and image fidelity. Compression algorithms based on the lossless models of Huffman, Adaptive Huffman, and Arithmetic coding are compared in terms of compression ratio and compression/decompression time requirements. High fidelity image reconstructions of JPEG and Fractal compressions are also included in the comparison. Results, for the images tested, indicate that if imperceptible losses in fidelity can be tolerated, then among the current versions of the algorithms tested, the JPEG results in higher compression with less process time.
Key concepts: Lossy compression, Lossless compression, Lossless JPEG, Image compression, JPEG, Data compression ratio, Fractal transform, Data compression