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An FPGA-oriented HW/SW Codesign of Lucy-Richardson Deconvolution Algorithm for Hyperspectral Images
| Content Provider | Semantic Scholar |
|---|---|
| Author | Avagian, Karine Orlandić, Milica Johansen, Tor Arne |
| Copyright Year | 2019 |
| Abstract | Hyperspectral images acquired during remote sensing are usually corrupted by optical blur and additive noise. This article considers a method to reduce the spatial blur in hyperspectral images by applying the Lucy-Richardson deconvolution algorithm. The algorithm is based on convolution with a point-spread function, which is assumed to be known. The complete algorithm is implemented as a HW/Sw Co-Design between the central processing unit and the programmable logic. The convolution, as a time consuming operation, is accelerated in an FPGA. When compared to the software implementation, a speed-up by a factor of 2.7 is achieved when using the accelerated HW/SW Co-Design implementation. Hyperspectral images synthetically distorted by a known Gaussian blur and an additive noise are used for testing. The images are then restored by applying the Lucy-Richardson deconvolution algorithm on each spectral band. |
| Starting Page | 1 |
| Ending Page | 6 |
| Page Count | 6 |
| File Format | PDF HTM / HTML |
| DOI | 10.1109/MECO.2019.8760174 |
| Alternate Webpage(s) | http://folk.ntnu.no/torarnj/Paper_MECO1.pdf |
| Alternate Webpage(s) | https://doi.org/10.1109/MECO.2019.8760174 |
| Journal | 2019 8th Mediterranean Conference on Embedded Computing (MECO) |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
