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Parallel multidimensional digital signal processing (mD-DSP) is defined as the application of parallel programming and multiprocessing to digital signal processing techniques to process digital signals that have more than a single dimension. The use of mD-DSP is fundamental to many application areas such as digital image and video processing, medical imaging, geophysical signal analysis, sonar, radar, lidar, array processing, computer vision, computational photography, and augmented and virtual reality. However, as the number of dimensions of a signal increases the computational complexity to operate on the signal increases rapidly. This relationship between the number of dimensions and the amount of complexity, related to both time and space, as studied in the field of algorithm analysis,

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  • Parallel multidimensional digital signal processing (en)
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  • Parallel multidimensional digital signal processing (mD-DSP) is defined as the application of parallel programming and multiprocessing to digital signal processing techniques to process digital signals that have more than a single dimension. The use of mD-DSP is fundamental to many application areas such as digital image and video processing, medical imaging, geophysical signal analysis, sonar, radar, lidar, array processing, computer vision, computational photography, and augmented and virtual reality. However, as the number of dimensions of a signal increases the computational complexity to operate on the signal increases rapidly. This relationship between the number of dimensions and the amount of complexity, related to both time and space, as studied in the field of algorithm analysis, (en)
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  • Parallel multidimensional digital signal processing (mD-DSP) is defined as the application of parallel programming and multiprocessing to digital signal processing techniques to process digital signals that have more than a single dimension. The use of mD-DSP is fundamental to many application areas such as digital image and video processing, medical imaging, geophysical signal analysis, sonar, radar, lidar, array processing, computer vision, computational photography, and augmented and virtual reality. However, as the number of dimensions of a signal increases the computational complexity to operate on the signal increases rapidly. This relationship between the number of dimensions and the amount of complexity, related to both time and space, as studied in the field of algorithm analysis, is analogues to the concept of the curse of dimensionality. This large complexity generally results in an extremely long execution run-time of a given mD-DSP application rendering its usage to become impractical for many applications; especially for real-time applications. This long run-time is the primary motivation of applying parallel algorithmic techniques to mD-DSP problems. (en)
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