JPEG2000 Wavelet Quality Scoring Without Full Decoding
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Solution Overview
Problem
Existing methods for measuring blurriness in JPEG2000 compressed images are computationally intensive and not suitable for low-latency applications, as they often require full decoding of the image and complex edge analysis.
Innovation Solution
A method that evaluates the presence of wavelet coefficients in specific sub-bands of the n-1 resolution layer of JPEG2000 tiles to determine a perceptual visual quality (PVQ) score, without full decoding, using empirically derived thresholds and weights to assess blurriness efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full decoding and complex edge analysis are performed to accurately measure blurriness, then measurement precision is improved, but device complexity and processing time increase
Solution Approach 1:
The patent extracts only the essential information needed for blurriness measurement by evaluating wavelet coefficients in specific sub-bands (particularly the LL sub-band) without performing full image decoding. This selective extraction of relevant coefficients maintains measurement accuracy while avoiding the computational burden of complete decoding and complex edge analysis.
Solution Approach 2:
The patent segments the blurriness measurement process by focusing on specific wavelet sub-bands and resolution layers (n-1 layer) rather than analyzing the entire image at full resolution. This segmentation allows accurate blurriness assessment through localized coefficient evaluation in frequency-domain sub-bands, significantly reducing computational complexity.
2Measurement precision
If full decoding is performed to evaluate image quality, then measurement precision is improved, but processing time and latency increase
Solution Approach 1:
The patent performs preliminary evaluation of wavelet coefficients at the n-1 resolution layer before full decoding is completed. By assessing blurriness indicators from the compressed wavelet representation itself, the system obtains quality metrics ahead of time, reducing latency without sacrificing measurement precision.
Solution Approach 2:
The patent extracts quality assessment information directly from the compressed wavelet coefficients without requiring complete decoding. By taking out only the necessary coefficient evaluations from specific sub-bands, the system achieves accurate blurriness measurement while minimizing processing time and latency.
3Measurement precision
If comprehensive image analysis is performed to maintain visual quality, then measurement precision is improved, but computational overhead increases
Solution Approach 1:
The patent applies local quality assessment by evaluating wavelet coefficients in specific sub-bands (particularly LL sub-band) and resolution layers rather than analyzing the entire image comprehensively. This localized approach maintains visual quality assessment accuracy by focusing on the most informative regions while significantly reducing computational overhead.
Solution Approach 2:
The patent performs partial action by evaluating only the necessary wavelet coefficients in specific sub-bands and resolution layers required for accurate blurriness measurement, rather than performing comprehensive analysis of all image data. This partial evaluation achieves sufficient measurement precision with reduced computational energy consumption.
Data Source
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AI summary
A method of detecting image quality in a wavelet transform-encoded image includes receiving wavelet transform-encoded image data partitioned into tiles, each tile partitioned into a number of subbands, evaluating a number of wavelets in fewer than the number of subbands, assigning a measure to each of the subbands evaluated for each tile, using the measures to determine a perceptual visual quality score for the image, and adjusting operation of the decoder based upon the perceptual visual quality score. A decoding system includes a memory to receive wavelet-transformed compressed image data having a predetermined number of subbands, and a decoder to determine a number of wavelet coefficients in a subset of the predetermined number of subbands, measure an amount of blur in the image data based upon the number of wavelet coefficients, and adjust a decoding process based upon the amount of blur.