Low-complexity Image and Video Coding Based on an Approximate Discrete Tchebichef Transform
This work addresses computational bottlenecks in real-time image and video coding applications, offering an incremental improvement over existing DTT methods.
The paper tackled the high computational complexity of the discrete Tchebichef transform (DTT) for image and video compression by introducing a low-complexity approximation, resulting in a 43.1% reduction in FPGA logic blocks and a 57.7% reduction in ASIC area-time compared to the exact DTT.
The usage of linear transformations has great relevance for data decorrelation applications, like image and video compression. In that sense, the discrete Tchebichef transform (DTT) possesses useful coding and decorrelation properties. The DTT transform kernel does not depend on the input data and fast algorithms can be developed to real time applications. However, the DTT fast algorithm presented in literature possess high computational complexity. In this work, we introduce a new low-complexity approximation for the DTT. The fast algorithm of the proposed transform is multiplication-free and requires a reduced number of additions and bit-shifting operations. Image and video compression simulations in popular standards shows good performance of the proposed transform. Regarding hardware resource consumption for FPGA shows 43.1% reduction of configurable logic blocks and ASIC place and route realization shows 57.7% reduction in the area-time figure when compared with the 2-D version of the exact DTT.