Ptychography Image Compression Using Overlap-Based Spatial Correlation
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Solution Overview
Problem
Existing ptychographic microscopy techniques face challenges in efficiently compressing and processing large amounts of data due to the need for numerous low-resolution images, leading to increased data storage and processing requirements.
Innovation Solution
A method and apparatus for compressing ptychography data by utilizing overlapping region information, where low-resolution images are encoded and decoded based on extracted Fourier domain information, and inverse-transformed to the spatial domain for improved spatial correlation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of low-resolution images are acquired to improve Fourier domain information coverage, then image reconstruction quality is improved, but data storage and processing requirements increase
Solution Approach 1:
The patent extracts and utilizes overlapping region information from multiple low-resolution images. By identifying and separating the overlapping regions containing redundant information from the non-overlapping regions, the method selectively processes only the necessary unique information, thereby reducing overall data volume while maintaining reconstruction quality.
Solution Approach 2:
The patent applies different processing strategies to different regions of the images. Overlapping regions are handled differently from non-overlapping regions, with the overlapping areas being used for correlation-based compression while non-overlapping areas retain their full information content. This localized differential processing optimizes the balance between data reduction and information preservation.
2Measurement precision
If a large number of low-resolution images are acquired to improve Fourier domain information coverage, then image reconstruction quality is improved, but processing complexity increases
Solution Approach 1:
The patent segments the processing task into distinct stages: extracting overlapping region information, calculating spatial correlations between overlapping and non-overlapping regions, compressing the data based on correlation coefficients, and finally reconstructing the high-resolution image. This segmentation transforms a complex monolithic processing task into manageable modular steps, reducing overall processing complexity.
Solution Approach 2:
The patent performs preliminary extraction of overlapping region information and calculation of spatial correlation coefficients before the main compression and reconstruction processes. By pre-processing and pre-calculating these correlation metrics, the method reduces the computational burden during the actual image reconstruction phase, thereby reducing overall processing complexity.
3Quantity of substance
If data compression is applied to reduce data volume, then storage requirements are reduced, but spatial correlation information may be lost
Solution Approach 1:
The patent employs feedback mechanisms where spatial correlation coefficients calculated from overlapping regions are used to guide the compression process. The correlation information is fed back into the compression algorithm to determine which data can be safely discarded and which must be retained, ensuring that compression does not eliminate critical spatial relationship information needed for accurate reconstruction.
Solution Approach 2:
The patent introduces spatial correlation coefficients as an intermediary element that bridges the overlapping and non-overlapping regions. These coefficients serve as mediators that preserve the spatial relationship information during compression, allowing the reconstruction process to recover accurate spatial correlations even when the original pixel data is compressed or discarded.
Data Source
AI summary
A method for compressing ptychography data according to a present disclosure, the method comprises: receiving at least two low-resolution images as input, wherein the at least two low-resolution images include a first image and a second image; encoding the first image; decoding the encoded first image; and encoding the second image based on the decoded first image, wherein the second image is encoded by referencing first overlapping region information extracted from the decoded first image and the second image.