TD-dAJC: A 2pJ/Pixel Time-Domain Weight and Integrating-MAC Based Direct-Analog-to-MJPEG Compression for Video Sensor Nodes

The increase in IoT applications has made cameras ubiquitous in various fields spanning from healthcare and autonomous vehicles to energy-constrained applications like battery-powered wearables. This proliferation has created a need for low-power camera modules for resource-constrained IoT nodes/edge devices. As the quality of images improves, these cameras produce a data deluge. Standard digital cameras generate data in the order of ~Gbps, which requires compressing the data within the camera module (e.g., SONY IMX 317) using lossy compression schemes like MJPEG or H.264. For instance, a 4K 12fps video generates around ~1 Gbps of data, which can be compressed to ~50 Mbps using MJPEG. Compared to H.264, MJPEG has lower latency and lower complexity, making it suitable for real-time edge applications. Standard digital data compression suffers from 1) high ADC energy consumption digitizing all samples, 2) Intermediate data storage requirements, and 3) huge computation power to compress the data, making it less desirable for edge cameras. The emergence of low-power camera imagers [1], such as the STM VD55G1 with power consumption as low as 3-10mW, has increased the demand for efficient compression techniques that minimize computational power as shown in Fig. 1(a) and (b).

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Publication Details

Published
2025-04-13
DOI
https://doi.org/10.1109/cicc63670.2025.10982732
Citations
1
Primary Topic
Sparse and Compressive Sensing Techniques
Type
article
Field-Weighted Citation Impact
1.33
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article

TD-dAJC: A 2pJ/Pixel Time-Domain Weight and Integrating-MAC Based Direct-Analog-to-MJPEG Compression for Video Sensor Nodes

Shreyas Sen, Gourab Barik, Yudhajit Ray, Harshit Naman
1 citations
Sparse and Compressive Sensing Techniques
1.33
article

TD-dAJC: A 2pJ/Pixel Time-Domain Weight and Integrating-MAC Based Direct-Analog-to-MJPEG Compression for Video Sensor Nodes

Shreyas Sen, Gourab Barik, Yudhajit Ray, Harshit Naman
article en
1 citations

Abstract

The increase in IoT applications has made cameras ubiquitous in various fields spanning from healthcare and autonomous vehicles to energy-constrained applications like battery-powered wearables. This proliferation has created a need for low-power camera modules for resource-constrained IoT nodes/edge devices. As the quality of images improves, these cameras produce a data deluge. Standard digital cameras generate data in the order of ~Gbps, which requires compressing the data within the camera module (e.g., SONY IMX 317) using lossy compression schemes like MJPEG or H.264. For instance, a 4K 12fps video generates around ~1 Gbps of data, which can be compressed to ~50 Mbps using MJPEG. Compared to H.264, MJPEG has lower latency and lower complexity, making it suitable for real-time edge applications. Standard digital data compression suffers from 1) high ADC energy consumption digitizing all samples, 2) Intermediate data storage requirements, and 3) huge computation power to compress the data, making it less desirable for edge cameras. The emergence of low-power camera imagers [1], such as the STM VD55G1 with power consumption as low as 3-10mW, has increased the demand for efficient compression techniques that minimize computational power as shown in Fig. 1(a) and (b).

Purdue University West Lafayette (US)
Affordable and clean energy
Openalex Percentile: Top 23%
Sparse and Compressive Sensing Techniques
1.33
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TD-dAJC: A 2pJ/Pixel Time-Domain Weight and Integrating-MAC Based Direct-Analog-to-MJPEG Compression for Video Sensor Nodes — Shreyas Sen, Gourab Barik, et al. · (2025) | TGRS Research Map | TGRS