The energy autonomy and the lifetime of battery-operated sensors are primary concerns in industrial, healthcare and IoT applications, in particular when a high amount of data needs to be sent wirelessly such as in Wireless Camera Sensors (WCS). Onboard real-time image compression is the appropriate solution to decrease the system’s energy. This paper proposes an optimized algorithm implementation tailored for PULP (Parallel Ultra Low Power) processors, that permits to shrink the image size and the data to transmit. Our optimized JPEG encoder based on a Fast-Discrete Cosine Transform (DCT) function is designed to achieve the best trade-off between energy consumption and image distortion. The parallel software implementation requires only 0.495 mJ per frame and can support up to 80 fps satisfying the most stringent requirements in WCSs applications without requiring a dedicated hardware accelerator.

Polonelli T., Battistini D., Rusci M., Brunelli D., Benini L. (2020). An Energy Optimized JPEG Encoder for Parallel Ultra-Low-Power Processing-Platforms. Springer [10.1007/978-3-030-37277-4_15].

An Energy Optimized JPEG Encoder for Parallel Ultra-Low-Power Processing-Platforms

Polonelli T.;Rusci M.;Brunelli D.;Benini L.
2020

Abstract

The energy autonomy and the lifetime of battery-operated sensors are primary concerns in industrial, healthcare and IoT applications, in particular when a high amount of data needs to be sent wirelessly such as in Wireless Camera Sensors (WCS). Onboard real-time image compression is the appropriate solution to decrease the system’s energy. This paper proposes an optimized algorithm implementation tailored for PULP (Parallel Ultra Low Power) processors, that permits to shrink the image size and the data to transmit. Our optimized JPEG encoder based on a Fast-Discrete Cosine Transform (DCT) function is designed to achieve the best trade-off between energy consumption and image distortion. The parallel software implementation requires only 0.495 mJ per frame and can support up to 80 fps satisfying the most stringent requirements in WCSs applications without requiring a dedicated hardware accelerator.
2020
Lecture Notes in Electrical Engineering
125
133
Polonelli T., Battistini D., Rusci M., Brunelli D., Benini L. (2020). An Energy Optimized JPEG Encoder for Parallel Ultra-Low-Power Processing-Platforms. Springer [10.1007/978-3-030-37277-4_15].
Polonelli T.; Battistini D.; Rusci M.; Brunelli D.; Benini L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/800225
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