ISO/IEC 23090-30:2026

• Abstract:

  This document specifies low latency, low complexity light detection and ranging (LiDAR) coding.

• Status: Published
• Publication Date: 26-Jul-2026
• ICS: 35.040.40 - Coding of audio, video, multimedia and hypermedia information
• Technical Committee: ISO/IEC JTC 1/SC 29 - Coding of audio, picture, multimedia and hypermedia information
• Drafting Committee: ISO/IEC JTC 1/SC 29 - Coding of audio, picture, multimedia and hypermedia information
• Current Stage: 6060 - International Standard published
• Start Date: 27-Jul-2026
• Due Date: 16-Mar-2026
• Completion Date: 27-Jul-2026

Overview

ISO/IEC 23090-30:2026 is an international standard that defines methods for the coded representation of immersive media-specifically focusing on low latency, low complexity light detection and ranging (LiDAR) coding. Developed by ISO/IEC Joint Technical Committee 1 (JTC 1), Subcommittee SC 29, this standard addresses the significant data storage and transmission challenges associated with LiDAR-based point clouds, which are increasingly used in modern 3D capture and rendering workflows.

By specifying efficient compression and coding techniques tailored for LiDAR point cloud data, ISO/IEC 23090-30:2026 enables real-time applications to process, transmit, and store large-scale 3D datasets with minimal delay and computational overhead. The standard is particularly relevant for applications that demand both immediate response and resource-efficient operations.

Key Topics

• Low Latency LiDAR Coding: The standard outlines methods to minimize delays in capturing, encoding, and reconstructing LiDAR point cloud data, supporting real-time use cases such as autonomous vehicles and industrial automation.
• Low Complexity Processing: Coding techniques are designed to be computationally efficient, allowing deployment on systems and devices with varying processing power and energy constraints.
• Point Cloud Attributes: It supports encoding not just 3D positions, but also LiDAR-derived attributes such as color, reflectance, opacity, material identifiers, and custom user-defined information.
• Data Structure Flexibility: Accommodates different point cloud formats, coordinate systems, and attribute coding schemes, ensuring interoperability in diverse technology ecosystems.
• Decoding Processes: Includes specifications for decoding LiDAR point cloud frames, attribute units, and maintaining consistency in output representations.
• Conventions and Syntax: The document carefully defines conventions for mathematical notation, operator precedence, and code syntax to ensure correct implementation.

Applications

ISO/IEC 23090-30:2026 provides substantial value in various industries by standardizing efficient LiDAR data handling:

• Autonomous Vehicles: Real-time LiDAR data processing is critical for navigation, obstacle detection, and situational awareness in both automotive and robotics sectors.
• Mapping and Cartography: Surveying, 3D terrain modeling, and urban planning applications benefit from fast, efficient compression and transmission of point cloud datasets.
• Industrial Automation: Manufacturing and warehousing utilize LiDAR point clouds for object detection, tracking, and safety monitoring, necessitating low complexity solutions for embedded systems.
• Immersive Media and Gaming: Virtual and augmented reality platforms rely on LiDAR-derived 3D environments, where low latency and efficient data handling are essential for interactive experiences.
• Smart Cities and Infrastructure Monitoring: Continuous LiDAR-based monitoring requires scalable, real-time data handling for infrastructure assessment and maintenance automation.

Related Standards

ISO/IEC 23090-30:2026 is part of the broader ISO/IEC 23090 series, which covers various aspects of immersive media coding. Related standards include:

• ISO/IEC 23090-5: Coded representation of point cloud data - Provides point cloud coding methods for various immersive applications.
• ISO/IEC 23090-2: Omnidirectional media format - Standardizes formats for omnidirectional video and audio, relevant in certain LiDAR-augmented media workflows.
• ISO/IEC 14496 Series (MPEG-4) - Offers foundational methods for multimedia content coding and representation.
• ISO/IEC 23008 Series (HEVC/H.265 and Extensions) - Advanced video coding standards that may supplement LiDAR data in hybrid immersive media systems.

Practical Value

Adopting ISO/IEC 23090-30:2026 ensures:

• Interoperability across diverse devices and platforms.
• Reduced transmission costs due to efficient compression.
• Enhanced scalability for real-time and embedded applications.
• Future-proof integration in evolving immersive media and 3D technology pipelines.

For organizations involved in LiDAR deployment, 3D data services, or immersive media, adherence to this standard streamlines development, increases efficiency, and strengthens market competitiveness through internationally recognized best practices.

International
Standard
ISO/IEC 23090-30
First edition
Information technology — Coded
2026-07
representation of immersive
media —
Part 30:
Low latency, low complexity light
detection and ranging (LiDAR)
coding
Reference number
© ISO/IEC 2026
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
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© ISO/IEC 2026 – All rights reserved
ii
Contents
Foreword . viii
Introduction . ix
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 General terms . 1
3.2 High-level syntax and entropy coding terms . 4
3.3 Tree structure terms . 7
3.4 Geometry coding terms . 7
3.5 Attribute coding terms . 7
4 Abbreviated terms and symbols . 8
4.1 Abbreviated terms . 8
4.2 Symbols . 8
4.3 Mnemonics . 9
5 Conventions . 9
5.1 General . 9
5.2 Numerical representation . 9
5.3 Arithmetic operators . 9
5.4 Logical operators . 10
5.5 Relational operators . 10
5.6 Bit-wise operators . 10
5.7 Assignment operators . 11
5.8 Range notation . 11
5.9 Mathematical functions . 11
5.9.1 General . 11
5.9.2 IntCos and IntSin . 12
5.9.3 IntSqrt . 12
5.9.4 IntRecipSqrt . 13
5.9.5 Div . 14
5.9.6 Morton . 14
5.9.7 FromMorton . 14
5.10 Order of operation precedence . 15
5.11 Named expressions . 15
5.11.1 General . 15
5.11.2 Scope . 16
5.11.3 Arguments of named expressions. 17
5.11.4 Sub-expressions . 17
5.11.5 Definitions with multiple statements . 17
5.11.6 Textual definitions . 17
5.12 Variables, syntax elements and tables . 17
6 Point cloud format and relationship to coded and output representations . 18
6.1 General format . 18
6.2 Attributes . 18
6.2.1 General . 18
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iii
6.2.2 Colour . 18
6.2.3 Opacity . 19
6.2.4 Reflectance . 19
6.2.5 Normal vector . 19
6.2.6 Material identifier . 19
6.2.7 Frame number/index. 19
6.2.8 User defined attributes . 20
6.3 Codec-derived attributes . 20
6.3.1 General . 20
6.3.2 Slice identifier . 20
6.3.3 Slice tag . 20
6.3.4 Canonical point order . 20
6.3.5 Point Morton order . 21
6.4 Coded point cloud format . 21
6.4.1 Sequence coordinate system . 21
6.4.2 Coding coordinate system . 22
6.4.3 Coded point cloud sequence . 22
6.4.4 Coded point cloud frame . 23
6.4.5 Slice of a coded point cloud frame . 23
6.4.6 Repetition of slices . 24
6.4.7 Relationship between tiles and slices . 24
6.4.8 Parameter sets. 25
6.5 Output point cloud format . 25
6.5.1 General . 25
6.5.2 Coordinate system . 25
6.5.3 Fixed-point conformance output . 25
6.5.4 Attributes . 26
6.5.5 Output point cloud sequence . 26
6.5.6 Output point cloud frame . 26
7 Syntax and semantics . 26
7.1 Method of specifying syntax in tabular form . 26
7.2 Specification of syntax functions and descriptors . 27
7.3 Syntax in tabular form . 28
7.3.1 General . 28
7.3.2 Parameter sets, ancillary data and byte alignment . 28
7.3.3 Geometry data unit . 35
7.3.4 Attribute data unit . 38
7.3.5 Defaulted attribute data unit syntax . 40
7.4 Semantics . 41
7.4.1 General . 41
7.4.2 Parameter sets, ancillary data and byte alignment . 41
7.4.3 Geometry data unit . 53
7.4.4 Attribute data unit . 55
7.4.5 Defaulted attribute data unit semantics . 55
8 Decoding process . 56
8.1 General decoding process . 56
8.2 Frame decoding processes . 56
8.2.1 General . 56
8.2.2 Frame counter . 56
8.3 Slice decoding processes . 56
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iv
8.3.1 General . 56
8.3.2 State variables . 56
8.3.3 Geometry decoding process . 57
8.3.4 Default attribute values . 57
8.3.5 Attribute decoding process . 57
8.3.6 At the end of a slice . 57
9 Slice geometry . 57
9.1 General . 57
9.2 Sensed point sequence . 58
9.2.1 General . 58
9.2.2 State variables and expressions . 58
9.2.3 Syntax element semantics . 59
9.2.4 Contextualization of decoding elevation_offset . 62
9.2.5 Reconstruction of sensed point positions . 65
9.2.6 Reconstructed output point positions . 74
9.2.7 Reconstructed output low latency attributes values . 74
9.2.8 Reconstructed point positions for attributes decoding . 74
10 Slice attributes . 74
10.1 General . 74
10.2 Point coordinates . 74
10.2.1 General . 74
10.2.2 Conversion to scaled angular coordinates . 75
10.3 Syntax element semantics . 75
10.4 Raw attribute decoding . 76
10.5 Attribute decoding using the region-adaptive hierarchical transform . 76
10.5.1 General . 76
10.5.2 Transform tree. 76
10.5.3 Coefficient order . 79
10.5.4 Coefficient scaling . 80
10.5.5 Transform domain prediction . 82
10.5.6 Inverse transform . 86
10.5.7 Reconstructed attribute values . 88
10.6 Attribute decoding using levels of detail . 88
10.6.1 General . 88
10.6.2 Syntax element semantics . 89
10.6.3 Reconstruction process . 89
10.6.4 State variables . 89
10.6.5 Levels of detail . 90
10.6.6 Predictor search . 96
10.6.7 Reconstruction of attribute values . 102
10.6.8 Prediction mode coding . 103
10.6.9 Scaling . 105
10.6.10 Coefficient prediction . 105
10.6.11 Transform coefficient weights . 106
10.6.12 Transform . 107
10.7 Attribute quantization parameters . 108
10.7.1 Syntax element semantics . 108
10.7.2 Per-point regional QP offset. 109
10.7.3 Attribute coefficient QP . 109
10.7.4 Definition of AttrQstep . 109
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11 Parsing process . 110
11.1 General . 110
11.2 Data unit buffer . 111
11.2.1 General . 111
11.2.2 State . 111
11.2.3 Initialization at the start of parsing a data unit . 112
11.2.4 Initialization at the start of parsing a geometry data unit footer . 112
11.2.5 Definition of DuNextBit . 112
11.3 Chunked bytestream parsing . 112
11.3.1 General . 112
11.3.2 Chunk syntax . 113
11.3.3 Chunk semantics . 113
11.3.4 State . 113
11.3.5 Span of chunked bytestream data within a data unit . 113
11.3.6 The chunk buffer . 114
11.3.7 State update at the start of every CBS . 114
11.3.8 Unpacking a single chunk . 114
11.3.9 Definition of ChunkNextAeBit . 114
11.3.10 Definition of ChunkNextBpBit . 115
11.3.11 Boundary between spliced chunked bytestreams . 115
11.3.12 Location of chunked bytestream boundaries . 116
11.4 General inverse binarization processes . 116
11.4.1 Parsing unsigned fixed-length codes (FL) . 116
11.4.2 Parsing signed fixed-length codes (FL+S) . 116
11.4.3 Parsing 𝑘𝑘-th order exp-Golomb codes (EGk) . 117
11.4.4 Parsing concatenated truncated unary and 𝑘𝑘-th order exp-Golomb codes (TU+EGk) . 117
11.4.5 Parsing concatenated bounded truncated unary and 𝑘𝑘-th order exp-Golomb codes
(BTU+EGk) . 117
11.4.6 Parsing signed concatenated truncated unary and 𝑘𝑘-th order exp-Golomb codes
(TU+EGk+S) . 118
11.4.7 Parsing signed concatenated bounded truncated unary and 𝑘𝑘-th order exp-Golomb
codes (BTU+EGk+S) . 118
11.4.8 Parsing signed concatenated asymmetrically bounded truncated unary and 𝑘𝑘-th
order exp-Golomb codes (ABTU+EGk+S) . 119
11.4.9 Parsing truncated unary codes (TU) . 120
11.4.10 Mapping process for signed codes . 120
11.4.11 Parsing ASN.1 object identifiers . 120
11.5 CABAC parsing processes . 121
11.5.1 Initialization . 121
11.5.2 Definition of AeReadBin . 121
11.5.3 Contextual probability models . 121
11.5.4 Arithmetic decoding engine . 125
11.6 Sensor Coding State . 127
11.6.1 State variable . 127
11.6.2 Initialization at the start of a GDU . 129
11.6.3 Initialization with decoded coarse position of first sensed point . 130
11.6.4 Update with azimuth_offset . 131
11.6.5 Update while decoding elevation_offset . 132
11.6.6 Update with sensed point coarse position . 132
11.7 Parsing state memorization and restoration . 133
© ISO/IEC 2026 – All rights reserved
vi
11.7.1 General . 133
11.7.2 Geometry data units . 133
11.7.3 Attribute data units . 134
11.7.4 Defaulted attribute data units . 134
12 OBUF parsing process . 134
12.1 General . 134
12.2 Creation of an OBUF instance . 134
12.2.1 Creation and initialization of OBUF trees . 135
12.2.2 Creation and initialization of an array of OBUF ACPMs . 136
12.3 Call and update of an OBUF instance . 136
12.3.1 Decode and update according to OBUF trees . 136
12.4 Decode of a bin based on an OBUF ACPM . 137
Annex A (normative) Profiles and levels . 139
Annex B (normative) Type-length-value encapsulated bytestream format . 144
Annex C (informative) Arithmetic encoding engine . 146
Annex D (informative) Index of named expressions and variables . 149
© ISO/IEC 2026 – All rights reserved
vii
Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are members
of ISO or IEC participate in the development of International Standards through technical committees
established by the respective organization to deal with particular fields of technical activity. ISO and IEC
technical committees collaborate in fields of mutual interest. Other international organizations, governmental
and non-governmental, in liaison with ISO and IEC, also take part in the work.
The procedures used to develop this document and those intended for its further maintenance are described
in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the different types of
document should be noted. This document was drafted in accordance with the editorial rules of the ISO/IEC
Directives, Part 2 (see www.iso.org/directives or www.iec.ch/members_experts/refdocs).
ISO and IEC draw attention to the possibility that the implementation of this document may involve the use of
(a) patent(s). ISO and IEC take no position concerning the evidence, validity or applicability of any claimed
patent rights in respect thereof. As of the date of publication of this document, ISO and IEC had received notice
of (a) patent(s) which may be required to implement this document. However, implementers are cautioned
that this may not represent the latest information, which may be obtained from the patent database available
at www.iso.org/patents and https://patents.iec.ch. ISO and IEC shall not be held responsible for identifying
any or all such patent rights.
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and expressions
related to conformity assessment, as well as information about ISO's adherence to the World Trade
Organization (WTO) principles in the Technical Barriers to Trade (TBT) see www.iso.org/iso/foreword.html.
In the IEC, see www.iec.ch/understanding-standards.
This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Subcommittee SC 29, Coding of
audio, picture, multimedia and hypermedia information.
A list of all parts in the ISO/IEC 23090 series can be found on the ISO and IEC websites.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html and www.iec.ch/national-
committees.
© ISO/IEC 2026 – All rights reserved
viii
Introduction
Advancements in 3D capturing and rendering technologies are enabling new applications and services in the
fields of assisted and autonomous driving, cartography, and other industrial processes. Point clouds captured
with LiDAR (Light Detection And Ranging) sensors, sometimes coupled with traditional camera sensors, have
arisen as one of the main representations for such applications. A point cloud frame consists of a set of 3D
points. Every point, in addition to having a 3D position, may also be associated with numerous other attributes
such as intensity, colour, timestamp, and classification. Such representations require a large amount of data,
which can be costly in terms of storage and transmission and are often used in real-time application which
requires fast processing of the point cloud data. This document provides the method for efficiently
compressing point cloud representations while ensuring low complexity and low latency constraints can be
met.
© ISO/IEC 2026 – All rights reserved
ix
International Standard ISO/IEC 23090-30:2026(en)

Information technology — Coded representation of
immersive media —
Part 30:
Low latency, low complexity light detection and ranging
(LiDAR) coding
1 Scope
This document specifies low latency, low complexity light detection and ranging (LiDAR) coding.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 8825-1 | Rec. ITU-T X.690, Information technology — ASN.1 encoding rules — Part 1: Specification of
Basic Encoding Rules (BER), Canonical Encoding Rules (CER) and Distinguished Encoding Rules (DER)
ISO/IEC 9834-1 | Rec. ITU-T X.660, Information technology — Procedures for the operation of object identifier
registration authorities — Part 1: General procedures and top arcs of the international object identifier tree
ISO/IEC 9834-8 | Rec. ITU-T X.667, Information technology — Procedures for the operation of object identifier
registration authorities — Part 8: Generation of universally unique identifiers (UUIDs) and their use in object
identifiers
ISO/IEC 23091-2, Information technology — Coding-independent code points — Part 2: Video
Recommendation ITU-T T.35, Procedure for the allocation of ITU-T defined codes for non-standard facilities
3 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https://www.iso.org/obp
— IEC Electropedia: available at https://www.electropedia.org/
3.1 General terms
3.1.1
point
fundamental element of a point cloud (3.1.2) comprising a position specified as Cartesian coordinates (3.1.8)
and zero or more attributes (3.1.19)
© ISO/IEC 2026 – All rights reserved
3.1.2
point cloud
unordered list of points (3.1.1)
3.1.3
point cloud sequence
sequence of one or more point clouds (3.1.2)
3.1.4
point cloud frame
point cloud (3.1.2) in a point cloud sequence (3.1.3)
3.1.5
coded point cloud frame
coded representation of a point cloud frame (3.1.4)
3.1.6
canonical point order
canonical decoding order
order of points (3.1.1) decoded from a slice (3.1.21) according to the decoding and parsing processes specified
in this document
3.1.7
bounding box
axis-aligned cuboid defining a spatial region that bounds a set of points (3.1.1)
3.1.8
coordinates
three scalar multiples of respective orthogonal XYZ (3.1.11) unit vectors with finite precision and
bounds that specify a position relative to a fixed reference
3.1.9
coordinates
a position specified as the radial distance 𝜌𝜌 from the V axis, an azimuth angle 𝜑𝜑 in the S-T plane and
an indexed elevation
3.1.10
coordinates
either STV (3.1.12) or scaled RPI (3.1.13) point coordinates used to code an attribute
3.1.11
XYZ (axes)
X, Y and Z axes, in that order, used to represent Cartesian coordinates (3.1.8)
3.1.12
STV (axes)
S, T and V axes, in that order, that are a sequence-dependent permutation of the XYZ axes (3.1.11); used to
represent the coded geometry (3.1.18)
3.1.13
RPI (axes)
R, P and I axes, in that order, used to represent angular coordinates (3.1.9)
3.1.14
sequence coordinate system
scaled and translated application-specific coordinate system that applies to an entire coded point cloud
sequence (3.1.3), and in which all points (3.1.1) have non-negative, fixed-point coordinates
© ISO/IEC 2026 – All rights reserved
3.1.15
coding coordinate system
scaled sequence coordinate system (3.1.14) that applies for an entire coded point cloud sequence (3.1.3), and in
which all points (3.1.1) have non-negative integer coordinates
3.1.16
slice coordinate system
translated coding coordinate system (3.1.15) that applies for a single slice (3.1.21), and in which all points
(3.1.1) in the slice have non-negative integer coordinates
3.1.17
sensing beam
sampler of point positions using angular coordinates by rays cast with a fixed elevation and from a point on
and rotating around the V axis at the angular origin
3.1.18
geometry
point positions (3.4.1) associated with a set of points (3.1.1)
3.1.19
attribute
scalar or vector property associated with each point (3.1.1) in a point cloud (3.1.2)
EXAMPLE Colour, reflectance, frame index, etc.
3.1.20
position
position
bit in a binary string or value, representing the factor 2
EXAMPLE The LSB has bit position 0.
3.1.21
slice
geometry and attributes for part of, or an entire, coded point cloud frame (3.1.5)
Note 1 to entry: the bounding boxes of any two slices can intersect.
3.1.22
tile
set of slices (3.1.21) identified by a common slice_tag syntax element value (3.2.15) whose geometry (3.1.18)
should be contained within a bounding box (3.1.7) specified in a tile inventory data unit
3.1.23
Morton code
non-negative integer obtained by interleaving the bits of three integers
3.1.24
Morton order
elements ordered according to their Morton code (3.1.23)
3.1.25
sparse array
array with fewer set elements than total addressable elements; u
...