Hierarchical Breakpoint Coding for Spatial Data Scalability
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Solution Overview
Problem
Existing image and video compression schemes struggle with efficiently encoding piecewise smooth spatial data sets, particularly at discontinuities, as they fail to effectively handle object boundaries and provide scalable and embedded representations of geometry information, leading to poor compression performance and resolution scalability.
Innovation Solution
A method involving a hierarchically organized set of breakpoints that identify discontinuities on arcs formed between points on a grid, with vertex and non-vertex breakpoints, where vertex breakpoints are encoded using embedded bit-plane coding and non-vertex breakpoints are inferred from coarser levels, allowing for scalable encoding and decoding of spatial data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If piecewise smooth spatial data sets are compressed using typical image compression schemes, then spatial redundancy in smooth regions is exploited, but compression performance deteriorates at the vicinity of discontinuities
Solution Approach 1:
The patent segments the spatial data set into smooth regions and discontinuity regions using a discontinuity detector. This segmentation allows different coding strategies to be applied to different regions: transform-based coding for smooth regions and geometry-adaptive coding for discontinuity regions, thereby resolving the contradiction between exploiting spatial redundancy and maintaining accuracy at discontinuities
Solution Approach 2:
The patent applies different coding qualities and methods to different parts of the data. Smooth regions receive standard transform-based coding while discontinuity regions receive enhanced geometry-adaptive coding with breakpoint detection and geometry-adaptive transforms. This local differentiation ensures high accuracy at discontinuities while maintaining overall compression efficiency
2Productivity
If segmentation is performed to compress smooth regions separately, then compression performance improves, but the representation of object boundaries becomes complex and non-scalable
Solution Approach 1:
The patent introduces a hierarchical dimension to boundary representation by organizing breakpoints into multiple levels. Coarse-level breakpoints capture major discontinuities while fine-level breakpoints capture detailed boundary features. This hierarchical structure enables scalable representation where boundaries can be approximated at coarse levels and refined at finer levels, reducing overall complexity
Solution Approach 2:
The patent embeds fine-level breakpoint information within the structure of coarse-level breakpoints. The hierarchical organization allows fine breakpoints to be nested within regions defined by coarse breakpoints, creating a compact nested representation that reduces the total number of boundary descriptors needed while maintaining accuracy
3Productivity
If a block based description of dominant orientation is used, then the transform responds to average orientation, but performance deteriorates at irregular or curved object boundaries
Solution Approach 1:
The patent segments boundaries into small atomic segments around detected breakpoints rather than using large blocks. This segmentation allows each segment to be described by local geometric parameters (breakpoint position, orientation, curvature) that accurately capture irregular and curved boundaries, eliminating the averaging effect of block-based approaches
Solution Approach 2:
The patent changes the parameter representation from block-based average orientation to breakpoint-based local geometry parameters. Each breakpoint is described by its position, local orientation, and curvature, allowing the transform to adapt to local boundary characteristics rather than being constrained by block-level average orientation, thereby achieving high accuracy for irregular and curved boundaries
Data Source
AI summary
The invention describes a method for representing geometry information to utilize for scalable coding of piecewise smooth spatial data sets. The method may also be applicable to vector data such as motion, where this data tends to exhibit piecewise smooth characteristics. The hierarchical geometry representation detailed in this invention is spatially scalable and amenable to embedded quantization and coding techniques. These features enable the geometry representation to be incorporated into highly scalable image coding schemes to attain efficient compression and output bit-streams with embedded resolution and quality scalability. Central elements of the invention are: the hierarchical representation of geometry information which describe points of discontinuity in the input data set; a rate-distortion driven estimation process to construct the geometry representation; a process to prioritize the geometry information in accordance to its influence on compression performance; and methods for efficient coding of the geometry information that facilitates resolution and quality scalability.