Abstract: A method and apparatus for compressing three-dimensional point cloud data is disclosed. In one aspect, a method for compressing three dimensional point cloud includes steps of retrieving three-dimensional point cloud data; providing one or more grids to the three-dimensional point cloud data; assigning one binary digit to each three-dimensional grid voxel containing said point cloud data and assigning the other binary digit to each three-dimensional grid voxel that does not have said point cloud data; converting the three-dimensional grid into two-dimensional tiles; and storing information of a plurality of binary strings in said two-dimensional tiles. In one embodiment, the step of storing information of a plurality of binary strings in said two-dimensional tiles includes a step of storing the number of repeating times of each binary digit in the binary strings. The method can significantly reduce memory space, as well as preserving small details of the point cloud.

Abstract: This invention relates to a method and apparatus for accurate compression and decompression of data. More specifically, this invention relates to a method and apparatus for compressing three dimensional spatial points (so called “point cloud”) and decompressing such data to produce an accurate point cloud. In one embodiment of the present invention, a level set based method is used to reconstruct a surface to approximate the surface of the point cloud. This reconstructed surface is defined implicitly as the zero level set of a function, which can be computed on a regular three-dimensional rectangular grid. Furthermore, the three-dimensional grid may be rearranged into a two-dimensional grid where the data are compressed and stored in a form of gradient. In order to recover the point cloud, the three-dimensional grid is rebuilt from the two-dimensional data and an interpolating algorithm on the implicit function is utilized to compute the points on the surface.

Abstract: A method and apparatus for compressing three-dimensional point cloud data is disclosed. In one aspect, a method for compressing three dimensional point cloud includes steps of retrieving three-dimensional point cloud data; providing one or more grids to the three-dimensional point cloud data; assigning one binary digit to each three-dimensional grid voxel containing said point cloud data and assigning the other binary digit to each three-dimensional grid voxel that does not have said point cloud data; converting the three-dimensional grid into two-dimensional tiles; and storing information of a plurality of binary strings in said two-dimensional tiles. In one embodiment, the step of storing information of a plurality of binary strings in said two-dimensional tiles includes a step of storing the number of repeating times of each binary digit in the binary strings. The method can significantly reduce memory space, as well as preserving small details of the point cloud.

Abstract: This invention relates to a method and apparatus for image processing, and more particularly, this invention relates to a method and apparatus for processing image data generated by bioanalytical devices, such as DNA sequencers. An object of the present invention is to remove artifacts such as noise, blur, background, non-uniform illumination, lack of registration, and extract pixel signals back to DNA-beads in a way that de-mixes pixels that contain contributions from nearby beads.

Abstract: This invention relates to a method and apparatus for accurate compression and decompression of data. More specifically, this invention relates to a method and apparatus for compressing three dimensional spatial points (so called “point cloud”) and decompressing such data to produce an accurate point cloud. In one embodiment of the present invention, a level set based method is used to reconstruct a surface to approximate the surface of the point cloud. This reconstructed surface is defined implicitly as the zero level set of a function, which can be computed on a regular three-dimensional rectangular grid. Furthermore, the three-dimensional grid may be rearranged into a two-dimensional grid where the data are compressed and stored in a form of gradient. In order to recover the point cloud, the three-dimensional grid is rebuilt from the two-dimensional data and an interpolating algorithm on the implicit function is utilized to compute the points on the surface.

Abstract: A system is disclosed providing accurate compression, storage, transmission and reconstruction of both simulated and empirical data representing terrain and other physical or hypothetical signals or surfaces, in one or multiple dimensions. In one embodiment, a gradient of an original surface is generated, and the data representing that gradient is compressed, then stored and/or transmitted. Reconstruction of the gradient yields an accurate representation of the original gradient. An alternative embodiment includes taking a second gradient of the original surface before compression, in which case reconstruction yields the second gradient, from which the first gradient can also be recovered.

Abstract: A method and apparatus for compression and restoration of images, videos, surfaces, curves and, generally, pixel-based data sets, including: feature-based quantization using a set of N isocontours; compressing each of these N contours using a level set-based compression of curves or surfaces—and/or combining the quantization with a conventional method for compression of surfaces; and decompressing the compressed data using a nonoscillatory reconstruction. The method is naturally multiscale, but does not use wavelets or other multiscale-basis functions. The method performs compression and decompression (1) without excessive computational complexity, even in the presence of topological changes such as merging or breaking of isocontours as the scale changes, (2) with excellent image fidelity, (3) without unacceptable artifacts such as ringing, blurring, or blocking, (4) with simple and natural grid based ways of calculating geometric features such as normals, principal curvatures.

Abstract: A system is disclosed providing accurate compression, storage, transmission and reconstruction of both simulated and empirical data representing terrain and other physical or hypothetical signals or surfaces, in one or multiple dimensions. In one embodiment, a gradient of an original surface is generated, and the data representing that gradient is compressed, then stored and/or transmitted. Reconstruction of the gradient yields an accurate representation of the original gradient. An alternative embodiment includes taking a second gradient of the original surface before compression, in which case reconstruction yields the second gradient, from which the first gradient can also be recovered.