Neuromorphic Vision Data Coding: Classifying and Reviewing the Literature

In recent years, visual sensors have been quickly improving towards mimicking the visual information acquisition process of human brain by responding to illumination changes as they occur in time rather than at fixed time intervals. In this context, the so-called neuromorphic vision sensors depart f...

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Bibliographic Details
Published in:IEEE access Vol. 13; pp. 14626 - 14657
Main Authors: Brites, Catarina, Ascenso, Joao
Format: Journal Article
Language:English
Published: Piscataway IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Cameras
Classification
Coding
Context
Data processing
Dynamic vision sensor
Encoding
event camera
Image acquisition
Image coding
Image sensors
neuromorphic vision data coding
Neuromorphics
Robot sensing systems
Sensors
spike camera
Taxonomy
Transform coding
Vision
Vision sensors
Visualization
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:In recent years, visual sensors have been quickly improving towards mimicking the visual information acquisition process of human brain by responding to illumination changes as they occur in time rather than at fixed time intervals. In this context, the so-called neuromorphic vision sensors depart from the conventional frame-based image sensors by adopting a paradigm shift in the way visual information is acquired. This new way of visual information acquisition enables faster and asynchronous per-pixel responses/recordings driven by the scene dynamics with a very high dynamic range and low power consumption. However, depending on the application scenario, the emerging neuromorphic vision sensors may generate a large volume of data, thus critically demanding highly efficient coding solutions in order applications may take full advantage of these new, attractive sensors' capabilities. For this reason, considerable research efforts have been invested in recent years towards developing increasingly efficient neuromorphic vision data coding (NVDC) solutions. In this context, the main objective of this paper is to provide a comprehensive overview of NVDC solutions in the literature, guided by a novel classification taxonomy, which allows better organizing this emerging field. In this way, more solid conclusions can be drawn about the current NVDC status quo, thus allowing to better drive future research and standardization developments in this emerging technical area.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2025.3528375