A system comprises an encoder configured to compress attribute and/or spatial information 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. In some embodiments, an encoder generates time-consistent patches for multiple version of the point cloud at multiple moments in time and uses the time-consistent patches to generate image based representations of the point cloud at the multiple moments in time.

In some examples, a method of decoding a point cloud includes decoding an initial QP value from an attribute parameter set. The method also includes determining a first QP value for a first component of an attribute of point cloud data from the initial QP value. The method further includes determining a QP offset value for a second component of the attribute of the point cloud data and determining a second QP value for the second component of the attribute from the first QP value and from the QP offset value. The method includes decoding the point cloud data based on the first QP value and further based on the second QP value.

In some examples, a method of decoding a point cloud includes decoding an initial QP value from an attribute parameter set. The method also includes determining a first QP value for a first component of an attribute of point cloud data from the initial QP value. The method further includes determining a QP offset value for a second component of the attribute of the point cloud data and determining a second QP value for the second component of the attribute from the first QP value and from the QP offset value. The method includes decoding the point cloud data based on the first QP value and further based on the second QP value.

A method for generating an output image from an input image and an input text instruction that specifies a location and a modification of an edit applied to the input image using a neural network is described. The neural network includes an image encoder, an image decoder, and an instruction attention network. The method includes receiving the input image and the input text instruction; extracting, from the input image, an input image feature that represents features of the input image using the image encoder; generating a spatial feature and a modification feature from the input text instruction using the instruction attention network; generating an edited image feature from the input image feature, the spatial feature and the modification feature; and generating the output image from the edited image feature using the image decoder.

A point cloud coding method includes obtaining description information of a bounding box size of a to-be-encoded point cloud and a normal axis of a to-be-encoded patch in the to-be-encoded point cloud, where the description information of the bounding box size of the to-be-encoded point cloud and the normal axis of the to-be-encoded patch are used to determine a tangent axis of the to-be-encoded patch and a bitangent axis of the to-be-encoded patch. The point cloud encoding method further includes encoding a syntax element into a bitstream, where the syntax element includes an index of the normal axis of the to-be-encoded patch and information for indicating the description information of the bounding box size of the to-be-encoded point cloud, and the syntax element is used to indicate the tangent axis of the to-be-encoded patch and the bitangent axis of the to-be-encoded patch.

A point cloud coding method includes obtaining description information of a bounding box size of a to-be-encoded point cloud and a normal axis of a to-be-encoded patch in the to-be-encoded point cloud, where the description information of the bounding box size of the to-be-encoded point cloud and the normal axis of the to-be-encoded patch are used to determine a tangent axis of the to-be-encoded patch and a bitangent axis of the to-be-encoded patch. The point cloud encoding method further includes encoding a syntax element into a bitstream, where the syntax element includes an index of the normal axis of the to-be-encoded patch and information for indicating the description information of the bounding box size of the to-be-encoded point cloud, and the syntax element is used to indicate the tangent axis of the to-be-encoded patch and the bitangent axis of the to-be-encoded patch.

A preprocessing technique for synthetic radar images. An embodiment of a method for preprocessing synthetic aperture radar images includes: receiving range-compressed radar data generated from raw radar image data on-board a satellite or an airborne vehicle; generating a preliminary SAR image by performing a pre-focusing on the range-compressed radar data; extracting image subsectors from the preliminary SAR image; transmitting the extracted image subsectors to an on-ground portion; reconstructing the range-compressed radar data pertaining to the extracted image subsectors; and making the range-compressed radar data pertaining to the extracted image subsectors available for a Nominal synthetic aperture radar processor, wherein the Nominal synthetic aperture radar processor is configured to generate a focused SAR image having a nominal value of image resolution that is higher than the resolution of the preliminary SAR image.

A preprocessing technique for synthetic radar images. An embodiment of a method for preprocessing synthetic aperture radar images includes: receiving range-compressed radar data generated from raw radar image data on-board a satellite or an airborne vehicle; generating a preliminary SAR image by performing a pre-focusing on the range-compressed radar data; extracting image subsectors from the preliminary SAR image; transmitting the extracted image subsectors to an on-ground portion; reconstructing the range-compressed radar data pertaining to the extracted image subsectors; and making the range-compressed radar data pertaining to the extracted image subsectors available for a Nominal synthetic aperture radar processor, wherein the Nominal synthetic aperture radar processor is configured to generate a focused SAR image having a nominal value of image resolution that is higher than the resolution of the preliminary SAR image.

A method and computer software for creating an encoded image and which can optionally include a method for decoding the encoded image. The encoded image is preferably formed from at least one symmetric image but can be formed from a plurality of symmetric images. Embodiments of the present invention can be performed with physical paper and writing utensils or can be performed via computer software. Embodiments of the present invention can be used for art authentication based on results obtained by decoding an image. In one embodiment, one or more encoded image elements can be revealed simultaneously. Optionally, however, encoded image elements can be caused to be revealed in a series that gives a sense of motion in a manner similar to that of motion picture animation.

A method and computer software for creating an encoded image and which can optionally include a method for decoding the encoded image. The encoded image is preferably formed from at least one symmetric image but can be formed from a plurality of symmetric images. Embodiments of the present invention can be performed with physical paper and writing utensils or can be performed via computer software. Embodiments of the present invention can be used for art authentication based on results obtained by decoding an image. In one embodiment, one or more encoded image elements can be revealed simultaneously. Optionally, however, encoded image elements can be caused to be revealed in a series that gives a sense of motion in a manner similar to that of motion picture animation.