In this work, we present a real-time embedded implementation of an algorithm dedicated to monitoring agricultural fields. This algorithm is based on normalized indices, such as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI). The problem of most algorithms in this context is real-time processing, especially when we talk about applications that require time precision. The proposed implementation is based on the application of a Hardware/Software Co-design approach. For the embedded platform, we used the heterogeneous system contains CPU and GPU type XU4 and TX1. In this context, we used the parallel programming language OpenMP to have an optimal embedded implementation. The results showed that we could process 66 images/s using a desktop, 20 images/s in the XU4, and 17 images/s for TX1.

在这项工作中，我们提出了一种专用于监视农业领域的算法的实时嵌入式实现。该算法基于归一化指标，例如归一化植被指数（NDVI）和归一化水分指数（NDWI）。在这种情况下，大多数算法的问题是实时处理，尤其是当我们谈论需要时间精度的应用程序时。提议的实现基于硬件/软件协同设计方法的应用。对于嵌入式平台，我们使用的异构系统包含CPU和GPU类型XU4和TX1。在这种情况下，我们使用并行编程语言OpenMP来实现最佳的嵌入式实现。结果表明，使用台式机可以处理66幅图像/秒，在XU4中可以处理20幅图像/秒，对于TX1可以处理17幅图像/秒。