Depth Codec Quadtree Compression for Real-Time Light Field Reconstruction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video codecs are inefficient in handling depth data for real-time, high-quality light field reconstruction, as they focus on color data and struggle with expensive real-time depth estimation and large data decoding.
Innovation Solution
A computer-implemented method for compressing and decompressing depth images using a quadtree data structure and the BC4-Wedged (BC4w) modeling function, which generates a runtime packed form with a desired maximum error, allowing for efficient spatial compression and decompression of high bit-depth depth images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional video codecs are used for depth data compression, then color data compression is optimized, but depth data compression performance deteriorates
Solution Approach 1:
The patent segments the depth image into multiple blocks and applies different compression strategies to different regions. The quadtree structure divides the image hierarchy into manageable segments, allowing selective compression of important depth regions while maintaining real-time processing capability.
Solution Approach 2:
The patent transforms depth values into a different parameter space using the BC4w modeling function, which represents depth data in terms of wedge-shaped regions defined by line equations and endpoint pairs. This parameter transformation enables more efficient compression while preserving depth accuracy.
2Manufacturing precision
If more depth data is compressed to improve reconstruction quality, then light field reconstruction quality improves, but decoding complexity and time increase
Solution Approach 1:
The patent extracts only the essential depth information needed for light field reconstruction by identifying and compressing only the changed regions using difference masks. This extraction approach reduces the amount of data that needs to be decoded while maintaining reconstruction quality.
Solution Approach 2:
The patent performs preliminary compression and organization of depth data into quadtree structures and BC4w parameter representations before transmission or storage. This preliminary action reduces the complexity of subsequent decoding operations during real-time reconstruction.
3Measurement precision
If high bit-depth depth images are compressed to maintain precision, then depth precision is preserved, but compression efficiency decreases
Solution Approach 1:
The patent changes the parameter representation of depth data from raw high-bit-depth values to BC4w model parameters (line coefficients, endpoint pairs, and palette indices). This parameter transformation maintains depth precision while significantly reducing the quantity of data that needs to be stored or transmitted.
Solution Approach 2:
Instead of directly compressing high-bit-depth depth values, the patent inverts the approach by representing depth information through geometric parameters (wedges defined by lines and endpoints) that require fewer bits to encode while preserving the same precision information.
Data Source
AI summary
Systems, methods, and articles of manufacture are disclosed that enable the compression of depth data and real-time reconstruction of high-quality light fields. In one aspect, spatial compression and decompression of depth images is divided into the following stages: generating a quadtree data structure for each depth image captured by a light field probe and difference mask associated with the depth image, with each node of the quadtree approximating a corresponding portion of the depth image data using an approximating function; generating, from the quadtree for each depth image, a runtime packed form that is more lightweight and has a desired maximum error; and assembling multiple such runtime packed forms into per-probe stream(s); and decoding at runtime the assembled per-probe stream(s). Further, a block compression format is disclosed for approximating depth data by augmenting the block compression format 3DC+(BC4) with a line and two pairs of endpoints.