Complex Hologram Index Coding for Real-Imaginary Compression
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Solution Overview
Problem
Existing hologram compression methods struggle to efficiently compress full-complex holograms while preserving the relationship between their real and imaginary parts, leading to low compression ratios and high computational complexity.
Innovation Solution
A coding method that reconstructs a full-complex hologram into a complex vector plane, divides it into unit regions, and transforms hologram pixels into integer indexes through quantization, followed by optimization and encoding using conventional image compression tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional hologram compression methods are used, then compression is achieved, but the relationship between real and imaginary parts is not preserved and compression ratio is low
Solution Approach 1:
The patent merges the real and imaginary parts of the complex hologram into a unified complex vector plane representation. By treating the hologram as a complex number system where real and imaginary components are intrinsically linked, the method preserves their relationship while enabling more efficient compression through joint processing rather than separate handling.
Solution Approach 2:
The patent changes the parameter representation from separate real and imaginary floating-point numbers to a unified complex vector plane with integer indexes. This parameter transformation allows the system to maintain the relationship between components while achieving higher compression ratios through integer-based indexing and quantization.
2Productivity
If full-complex hologram is compressed without reconstruction, then processing is simpler, but compression efficiency is poor
Solution Approach 1:
The patent performs preliminary reconstruction of the full-complex hologram into a complex vector plane before compression. By pre-processing the hologram data to establish the relationship between real and imaginary parts in advance, the subsequent compression operation becomes more efficient, achieving better compression ratios without excessive computational overhead during the actual compression phase.
Solution Approach 2:
The patent segments the complex vector plane into multiple unit regions and applies quantization to each region. This segmentation allows for localized optimization of compression parameters and enables parallel processing, reducing overall computational complexity while improving compression efficiency through region-specific processing.
3Manufacturing precision
If high resolution is maintained, then hologram quality is preserved, but data size is large
Solution Approach 1:
The patent changes the data representation parameters from high-precision floating-point numbers to integer indexes in a quantized complex vector plane. This parameter transformation maintains sufficient hologram quality for reconstruction while dramatically reducing data size, as integer indexes require fewer bits than floating-point representations.
Solution Approach 2:
The patent creates a compressed index representation that serves as a surrogate for the full-resolution hologram data. Instead of storing and processing the complete high-resolution complex hologram, the system stores compact integer indexes that can be used to reconstruct the hologram, effectively copying only the essential information needed for quality reconstruction.
Data Source
AI summary
Provided is a coding method for compressing a complex hologram, in which the coding method includes: (b) creating a complex vector plane divided into unit regions, and giving an index to each unit region of the complex vector plane; (c) projecting the complex hologram to the complex vector plane by regarding the complex hologram as a complex vector, and assigning the index given to the unit region of the projected complex vector plane as a complex index of the complex hologram; and (f) encoding the complex hologram assigned with the complex index. According to the method described above, the full-complex hologram is reconstructed into one piece of index information using the complex vector plane to code the full-complex hologram, such that the hologram can be efficiently compressed while preserving a relationship between a real hologram and an imaginary hologram.