A method for point cloud decoding includes receiving a bitstream. The method also includes decoding the bitstream into multiple frames that include pixels. Certain pixels of the multiple frames correspond to points of a three-dimensional (3D) point cloud. The multiple frames include a first set of frames that represent locations of the points of the 3D point cloud and a second set of frames that represent attribute information for the points of the 3D point cloud. The method further includes reconstructing the 3D point cloud based on the first set of frames. Additionally, the method includes identifying a first portion of the points of the reconstructed 3D point cloud based at least in part on a property associated with the multiple frames. The method also includes modifying a portion of the attribute information. The portion of the attribute information that is modified corresponds to the first portion of the points.

The present disclosure relates to an image processing device and an image processing method for generating a celestial sphere image such that the pixels near the poles of the sphere are kept from increasing in density when the image is mapped to the sphere surface.

An encoder encodes, with respect to an omnidirectional image generated by equidistant cylindrical projection to include a top image, a middle image, and a bottom image in a vertical direction, the middle image into an encoded stream at a high resolution, and the top image and the bottom image into encoded streams at a resolution lower than the high resolution. This disclosure is applicable to image display systems, among others.

The current document is directed to a dimensional shuffle transform (“DST”) that maps a 3D space to a one-dimensional space that preserves 3D neighborhoods within 1D neighborhoods within an implicit recursive hierarchical structure. The search for points in a 3D subspace is reduced, by the DST, to one or more searches in the transformed 1D space. The search is performed by either recursive decomposition of the 3D region indexed by the transform into subspaces, exploiting the transformed space structure, or by direct indexing into the region of interest. The searches over the subspaces generated by recursive decomposition are independent from one another, providing many opportunities for a variety of parallel, DST-enabled search methods.

A system comprises an encoder configured to compress attribute information and/or spatial for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. To compress the attribute and/or spatial information, the encoder is configured to convert a point cloud into an image based representation. Also, the decoder is configured to generate a decompressed point cloud based on an image based representation of a point cloud. Additionally, an encoder is configured to signal and/or a decoder is configured to receive a supplementary message comprising volumetric tiling information that maps portions of 2D image representations to objects in the point. In some embodiments, characteristics of the object may additionally be signaled using the supplementary message or additional supplementary messages.

A method for coding information of a point cloud comprises obtaining the point cloud including a set of points in a three-dimensional space; partitioning the point cloud into a plurality of objects and generating occupancy information for each of the plurality of objects; and encoding the occupancy information by taking into account the distance between the plurality of objects.

A three-dimensional data creation method includes: creating first three-dimensional data from information detected by a sensor; receiving encoded three-dimensional data that is obtained by encoding second three-dimensional data; decoding the received encoded three-dimensional data to obtain the second three-dimensional data; and merging the first three-dimensional data with the second three-dimensional data to create third three-dimensional data.

A method and device for decoding a point cloud using octree partitioning and a predictive tree include obtaining the point cloud. A bounding box of the point cloud is determined. Octree nodes are generated by partitioning the bounding box using octree partitioning. The predictive tree is generated for points in at least one octree node of the octree nodes. A transform is applied to the predictive tree. The points in the at least one octree node are decoded using the predictive tree.

An apparatus includes a communication interface and a processor operably coupled to the communication interface. The communication interface receives a plurality of tracks in a compressed bitstream. The processor identifies an atlas track corresponding to a point cloud compression (PCC) component and identifies a set of first component tracks that is referenced by the atlas track and at least one second component track, each of the at least one second component track is an alternative version of a first component track of the set of first component tracks. The processor also determines which of the set of first component tracks and the at least one second component track are appropriate versions of the PCC component. The processor further decodes the appropriate version of the PCC component from among the set of first component tracks and the at least one second component track.

A three-dimensional data storage method includes: acquiring one or more units in which an encoded stream generated by encoding point cloud data is stored; and storing the one or more units into a file. The storing includes storing, in control information for the file, information indicating that data stored in the file is data generated by encoding the point cloud data.

A method for encoding a digital hologram represented by values associated respectively with pixels in a plane defining the digital hologram includes forming matrix blocks associated respectively with regions composed of contiguous pixels, each matrix block containing elements determined as a function of the values of the pixels in the region associated with the respective matrix block, applying to each of the matrix blocks a space-frequency transformation to obtain, for each matrix block, a set of coefficients respectively corresponding to different two-dimensional spatial frequencies within the respective matrix block, constructing two-dimensional structures each including coefficients from sets of coefficients and associated with two-dimensional spatial frequencies meeting a criterion that is dependent on the two-respective dimensional structure, and encoding the constructed two-dimensional structures.