Pruned Discrete Tchebichef Transform Approximation for Image Compression

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.