| Autor: |
Fakhreddine Zayer, Baker Mohammad, Hani Saleh, Gabriele Gianini |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 8, Pp 127569-127580 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2020.3004184 |
| Popis: |
Anisotropic-diffusion is a commonly used signal preprocessing technique that allows extracting meaningful local characteristics from a signal, such as edges in an image and can be used to support higher-level processing tasks, such as shape detection. This paper presents a fully scalable CMOS-RRAM architecture of an edge-aware-anisotropic filtering algorithm aimed at computer vision applications. The CMOS circuitry controls the scale-space image data to perform pseudo-parallel in-memory computing and nonlinear processing through RRAM crossbar. The arithmetic operations for in-memory computation of brightness gradients are efficiently accumulated to produce the enhanced image in several iterations. The proposed architecture uses single RRAM as a computing and storage element to perform both arithmetic operations and accumulations. Thanks to the in-memory computation, memory accesses and arithmetic operations are reduced by 64% and 92%, respectively, compared to traditional digital implementations. This, in turn, results in a potential reduction of power and area costs of about 75% and 85%, respectively. The processing time is also reduced by 67%. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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