Adaptive Quantization Apparatus for Statistical Image Data Preservation
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Solution Overview
Problem
Conventional quantization methods for statistical images, which use a uniform quantization parameter for all pixels, fail to maintain statistical properties due to differences in data sparsity, leading to loss of information in areas with varying population densities.
Innovation Solution
A quantization apparatus that derives a quantization parameter specific to each pixel based on its value, allowing for variable quantization widths to maintain statistical properties by converting statistical data into pixel values associated with positions in a real space image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the same quantization parameter is used for all pixels in the statistical image, then the image quality is improved, but the statistical properties are not maintained
Solution Approach 1:
The patent applies local quality by deriving different quantization parameters for different regions or pixels in the statistical image based on their local statistical characteristics. Instead of using a uniform quantization parameter across the entire image, the system analyzes local data density and variability to assign appropriate quantization parameters to each pixel or region, thereby maintaining both image quality and statistical properties locally.
Solution Approach 2:
The patent implements dynamics by making the quantization parameter adaptive rather than static. The quantization parameter is dynamically determined based on local statistical characteristics such as data density and variability. This allows the quantization process to adapt to different regions of the statistical image, preserving statistical properties while maintaining acceptable image quality.
2Device complexity
If a uniform quantization parameter is applied, then the processing complexity is reduced, but the statistical differences between regions are lost
Solution Approach 1:
The system applies local quality by analyzing local statistical characteristics (such as data density and variability) in different regions of the statistical image and deriving quantization parameters accordingly. This ensures that regions with different statistical properties are quantized appropriately, preserving statistical differences while maintaining manageable processing complexity through localized analysis rather than global optimization.
Solution Approach 2:
The patent applies parameter changes by modifying the quantization parameter based on local statistical characteristics. Instead of using a fixed quantization parameter, the system adjusts the parameter values according to local data density and variability, allowing the quantization process to adapt to different regions and preserve statistical differences without requiring overly complex processing.
3Productivity
If the quantization parameter is set according to high-density areas, then compression efficiency is improved, but low-density areas lose statistical detail
Solution Approach 1:
The patent applies local quality by deriving quantization parameters based on local data density characteristics. High-density areas receive quantization parameters optimized for compression efficiency, while low-density areas receive parameters that preserve statistical detail. This localized approach ensures that each region is quantized according to its specific characteristics, balancing compression efficiency with statistical detail preservation.
Solution Approach 2:
The system implements parameter changes by adjusting the quantization parameter values according to local data density. In high-density areas, larger quantization steps are used to improve compression efficiency, while in low-density areas, smaller quantization steps are applied to maintain statistical detail. This dynamic parameter adjustment resolves the contradiction between compression efficiency and statistical detail preservation.
Data Source
AI summary
A quantization apparatus includes: an imaging unit that converts statistical data at a position in a real space into a pixel value of a coordinate, which is associated with the position, in an image; and a derivation unit that derives a quantization parameter corresponding to a quantization width of the pixel value for each of one or more positions in the real space with respect to a part or a whole of the image. The quantization apparatus may further include a purpose acquisition unit that acquires information indicating a purpose related to statistics. The derivation unit may derive the quantization parameter corresponding to the quantization width that is larger as the pixel value is larger.