An efficient and highly scalable listless SPIHT image compression framework
Abstract The SPIHT is a powerful image compression algorithm. It has reasonable complexity and produces a quality (or rate) scalable bit-stream. Unfortunately, SPIHT fails to explore the multi-resolution nature of the wavelet transform as it doesn't support resolution scalability. Moreover, it requires a huge computer memory with complex memory management because it utilizes lists with a memory of about 2.5 the image size. This paper proposes three related algorithms. The first algorithm modifies SPIHT to reduce its complexity and improve its efficiency, especially at low bit rates. The second algorithm is the main contribution of the paper. It provides a simultaneous solution to the memory and scalability problems of SPIHT. Memory is reduced by utilizing state marker bits of an average size of 2.5 bits per pixel instead of the lists. Resolution scalability is maintained by coding the resolution levels in incremental order. Consequently, the resulting bit-stream can be easily and efficiently decompressed at numerous qualities and resolutions. This feature is very valuable for modern users that have diverse access bandwidths and display capabilities. The third algorithm has slightly lower complexity and memory than the second algorithm but has slightly lower performance. Another important attribute of our algorithms is that they have a very little increment in complexity in comparison to the original SPIHT algorithm. In contrast, the existing solutions have much more complexity and memory resources.
| Main Authors: | , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología
2022
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| Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-64232022000200173 |
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