Abstract
Processing and analysis of Very High Resolution (VHR) satellite images provide a mass of crucial information, which can be used for urban planning, security issues or environmental monitoring. However, they are computationally expensive and, thus, time consuming, while some of the applications, such as natural disaster monitoring and prevention, require high efficiency performance. Fortunately, parallel computing techniques and embedded systems have made great progress in recent years, and a series of massively parallel image processing devices, such as digital signal processors or Field Programmable Gate Arrays (FPGAs), have been made available to engineers at a very convenient price and demonstrate significant advantages in terms of running-cost, embeddability, power consumption flexibility, etc. In this work, we designed a texture region segmentation method for very high resolution satellite images by using the level set algorithm and the multi-kernel theory in a high-abstraction C environment and realize its register-transfer level implementation with the help of a new proposed high-level synthesis-based design flow. The evaluation experiments demonstrate that the proposed design can produce high quality image segmentation with a significant running-cost advantage.
Highlights
Remote sensing techniques are increasingly used in geological exploration, natural disaster prevention, monitoring, etc
Zeng Yonghong [7] presented an efficient Intellectual Property (IP) core design methodology to implement a real-time image processing application, such as the Normalized Product correlation (NProd) image matching algorithm; Chiesi et al [2] proposed a new non-conventional technique based on Fuzzy Deconvolution for Scattering Center Detection (F-SCD) and its embedded implementation for real-time deployment in an Sensors 2016, 16, 771; doi:10.3390/s16060771
A highly parallel image segmentation algorithm dedicated to very high resolution satellite images [14,15] is prototyped and validated, the implementation process of this algorithm into the register-transfer level is described, a high-level design flow is developed by using the recent high-level synthesis tools to improve the development productivity and maintainability of the design, a series of optimizations are sequentially made in the routine level to reduce the running-cost of the design; the experiments demonstrate that a significant performance improvement is achieved
Summary
Remote sensing techniques are increasingly used in geological exploration, natural disaster prevention, monitoring, etc. A highly parallel image segmentation algorithm dedicated to very high resolution satellite images [14,15] is prototyped and validated, the implementation process of this algorithm into the register-transfer level is described, a high-level design flow is developed by using the recent high-level synthesis tools to improve the development productivity and maintainability of the design, a series of optimizations are sequentially made in the routine level to reduce the running-cost of the design; the experiments demonstrate that a significant performance improvement is achieved.
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