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Pruned Discrete Tchebichef Transform Approximation for Image Compression

机译:修剪的离散Tchebichef变换逼近用于图像压缩

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Discrete transforms are widely employed in image and video coding standards. Because the discrete Tchebichef transform (DTT) presents good energy compaction properties, its usage in image compression schemes has been studied as an alternative to the discrete cosine transform (DCT). Embedded applications, such as wireless visual sensor networks, exhibit severe energy consumption restrictions. In such context, low-complexity discrete transforms approximations have been employed for data compression to save energy and bandwidth. In the current work, we proposed a set of low-complexity pruned DTT approximations suitable for low-power embedded systems. The introduced methods are obtained by pruning the state-of-art DTT approximation, being applicable in the image and video coding context. VLSI architectures were realized and the measured results assessed, showing that the proposed pruned methods present significant reduction in computational costs when compared to the DCT. At the same time, the performance is maintained roughly the same, suggesting a favorable trade-off for low-power applications.
机译:离散变换广泛应用于图像和视频编码标准。由于离散Tchebichef变换(DTT)具有良好的能量压缩特性,因此已经研究了它在图像压缩方案中的使用,以替代离散余弦变换(DCT)。诸如无线视觉传感器网络之类的嵌入式应用程序显示出严格的能耗限制。在这种情况下,低复杂度离散变换近似已被用于数据压缩以节省能量和带宽。在当前的工作中,我们提出了一组适用于低功耗嵌入式系统的低复杂度修剪DTT近似值。通过修剪最新的DTT近似值可获得引入的方法,这些方法适用于图像和视频编码环境。实现了VLSI架构并评估了测量结果,表明与DCT相比,所提出的修剪方法显着降低了计算成本。同时,性能保持大致相同,这建议在低功耗应用中进行权衡。

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