Compressed Image Pixel Error Estimation
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Solution Overview
Problem
Existing methods for estimating reconstruction accuracy of images generated from compressed data are computationally costly, as they often require comparing reconstructed images with correct images generated using different methods.
Innovation Solution
An information processing method that identifies pixels in a compressed image likely to cause reconstruction errors based on pixel values or the size of the target structure, allowing for estimation of reconstruction accuracy at a relatively low computational cost without generating reconstructed images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reconstruction accuracy estimation is performed by comparing reconstructed images with correct images, then measurement precision of reconstruction accuracy is improved, but computational cost increases significantly
Solution Approach 1:
The patent extracts only the essential information needed for accuracy estimation from the compressed image, specifically identifying pixels with abnormal characteristics (extreme pixel values or structural anomalies) without performing full reconstruction. This selective extraction approach allows accuracy assessment using minimal computational resources while maintaining measurement precision.
Solution Approach 2:
Instead of generating complete reconstructed images for comparison, the patent creates a simplified representation by copying only the compressed image data and marking suspected error pixels. This copying approach enables accuracy estimation through direct analysis of compressed image characteristics rather than through computationally intensive reconstruction and comparison processes.
2Measurement precision
If full reconstruction process is performed to assess accuracy, then measurement precision is improved, but productivity decreases due to time consumption
Solution Approach 1:
The patent segments the accuracy estimation task by dividing the compressed image into individual pixels and evaluating each pixel's characteristics independently. This segmentation allows parallel processing and significantly reduces the time required compared to performing full reconstruction, while still providing comprehensive accuracy measurement through systematic pixel-by-pixel analysis.
Solution Approach 2:
The patent performs preliminary identification of suspicious pixels in the compressed image before any reconstruction occurs. By pre-marking pixels with abnormal characteristics (extreme values or structural anomalies), the system prepares the data structure needed for accuracy assessment without executing the time-consuming reconstruction process, thus maintaining both precision and productivity.
Data Source
AI summary
An information processing method performed using a computer, includes: acquiring a compressed image, in which information regarding wavelength bands is compressed, and identifying, based on at least one of (1) pixel values of pixels included in the compressed image, or (2) a size of a structure of a target represented by the compressed image, at least one first pixel that is included in the compressed image and that is estimated to cause a reconstruction error in images corresponding to the respective wavelength bands, the images being reconstructed from the compressed image.