implementation of SPIHT (without Arithmatic coding stage)

资 源 简 介

matlab implementation of SPIHT (without Arithmatic coding stage).％ Performance evaluation : this toolbox VS. SPIHT％ Test image: lena512.raw％ bpp SPIHT(dB) This code(dB)％ 0.1000 29.8107 29.3202％ 0.2000 32.7202 32.2514％ 0.3000 34.5479 34.0331％ 0.4000 35.842

详 情 说 明

In the provided text, we have the MATLAB implementation of the Set Partitioning in Hierarchical Trees (SPIHT) algorithm, specifically without the Arithmetic Coding stage. We also have information about the performance evaluation of this toolbox compared to the original SPIHT algorithm. The test image used for evaluation is lena512.raw.

Let's take a look at the results for different bit rates (bpp) for both SPIHT and this code:

- At a bit rate of 0.1000, SPIHT achieves a performance of 29.8107 dB, while this code achieves a performance of 29.3202 dB.

- For a bit rate of 0.2000, SPIHT achieves 32.7202 dB, whereas this code achieves 32.2514 dB.

- When the bit rate is increased to 0.3000, SPIHT achieves a performance of 34.5479 dB, while this code achieves 34.0331 dB.

- At a bit rate of 0.4000, SPIHT achieves 35.8422 dB, whereas this code achieves 35.4857 dB.

- Continuing to increase the bit rate to 0.5000, SPIHT achieves a performance of 36.8623 dB, while this code achieves 36.5939 dB.

- At a bit rate of 0.6000, SPIHT achieves 37.6650 dB, whereas this code achieves 37.3759 dB.

- For a bit rate of 0.7000, SPIHT achieves a performance of 38.2581 dB, while this code achieves 38.0491 dB.

- At a bit rate of 0.8000, SPIHT achieves 38.9390 dB, whereas this code achieves 38.7058 dB.

- Finally, for a bit rate of 0.9000, SPIHT achieves a performance of 39.5218 dB, while this code achieves 39.3437 dB.

These results provide insights into the performance of the SPIHT algorithm and the corresponding implementation in MATLAB without the Arithmetic Coding stage.