Abstract
Computation Unit plays vital role in satellite image processing systems. Division is the least commonly used of the four basic arithmetic operations because it is too difficult to utilise. The primitive use of division is an iterative subtraction. Approximate computing is a new trend in digital design that forgoes the need for accurate computation in favour of increased speed and power performance. For error tolerant application approximate computing can reduce design complexity while increasing performance and power efficiency. This work provides new approximation compressors as well as an approach for using them to create efficient approximate multipliers. We have summed up approximate multipliers for different operand lengths using the proposed method. Detailed simulation results show that the Modified architectures achieves significant improvements in accuracy and efficiency as well as reduced area, power and latency compared to existing multiplier designs to improve the compressor efficiency recommendations are based on approximate multiplier system. The Proposed system is suitable for satellite image processing and radar image processing system with high accuracy. The proposed system is implemented in canny edge detection algorithm for measuring its performance.
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Communicated by: H. Babaie
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Pazhani, A.A.J. Computation unit architecture for satellite image processing systems. Earth Sci Inform 15, 185–195 (2022). https://doi.org/10.1007/s12145-021-00715-1
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DOI: https://doi.org/10.1007/s12145-021-00715-1