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In this paper we present the Sum of Absolute Difference algorithm (SAD) implementation on FPGA device.
The paper presents SAD implementation in Handel-C and its evaluation to the PixelStreams module.
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In HEVC hardware implementation, SAD calculation becomes a bottleneck due to the large size of a CTU (64 × 64) and various PU partitions due to the introduction of asymmetric motion partitioning (AMP).
By concerning the importance of SAD calculation in real hardware implementation, a SAD-based complexity measurement is introduced in this paper in the need of evaluating the proposed algorithm and other works.
Several works have addressed the issue of SAD calculation [19 21], and many new SAD architectures and implementations are introduced to utilize the amount of data reuse for SAD costs.
Firstly, SAD-based methods are the most appropriate to real-time implementation due to its low complexity (only summations and absolute values calculations) [18].
He may be a little sad but he will still take the responsibility and ownership for successful implementation.
Table 1 shows the spectral angle distance (SAD) [3] between the most similar endmembers detected by the original ENVI implementation (using the supervised -dimensional visualization tool to derive the final set of endmembers), the PPI approximation described in Section 3 (implemented in the C++ programming language), and our FPGA-based implementation.
Sad, so sad.
Sad, sad day".
Full implementation begins this fall.
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