Deblocking Filtering Strength Control for High-Luminance Image Regions
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Solution Overview
Problem
Existing deblocking filtering technologies struggle to effectively reduce block distortion in high-luminance portions of both standard dynamic range (SDR) and high dynamic range (HDR) signals, while maintaining compression efficiency.
Innovation Solution
An encoding and decoding device that incorporates a deblocking filtering unit, which adjusts filtering strength based on the luminance signal level and quantization parameter of the reconstructed image, thereby enhancing filtering effectiveness in high-luminance regions without compromising compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If deblocking filtering is applied to reduce block distortion, then image quality is improved, but compression efficiency deteriorates
Solution Approach 1:
The patent applies different filtering strengths to different regions of the image based on their luminance characteristics. High-luminance regions receive stronger filtering to reduce block distortion, while low-luminance regions receive weaker filtering to preserve compression efficiency. This local adaptation resolves the contradiction by tailoring filtering intensity to local image properties rather than applying uniform filtering across the entire image.
Solution Approach 2:
The patent dynamically adjusts the filtering strength parameter based on the luminance signal level of the reconstructed image. The filtering strength is not fixed but varies adaptively according to the image content characteristics. This dynamic adjustment allows the system to optimize between image quality improvement and compression efficiency preservation by responding to actual image conditions.
2Manufacturing precision
If filtering strength is increased to reduce block distortion in high-luminance portions, then image quality is improved, but compression efficiency deteriorates
Solution Approach 1:
The patent specifically targets high-luminance portions of the image for enhanced filtering while maintaining weaker filtering in low-luminance portions. This localized approach ensures that compression efficiency is preserved in regions where it matters most (low-luminance areas) while still improving image quality in high-luminance areas where block distortion is most noticeable.
Data Source
AI summary
An encoding device 1 includes: a transformation unit 13 configured to calculate an orthogonal transform coefficient by performing an orthogonal transformation process on a residual image indicating a difference between the input image and a predicted image of the input image; a quantization unit 14 configured to generate a quantization coefficient by quantizing the orthogonal transform coefficient on the basis of a quantization parameter; an entropy encoding unit 24 configured to generate encoded data by encoding the quantization coefficient; an image decoding unit 10 configured to restore an orthogonal transform coefficient from the quantization coefficient on the basis of the quantization parameter and generate a reconstructed image by adding the predicted image to a residual image restored by performing inverse orthogonal transformation on the orthogonal transform coefficient; and a deblocking filtering unit 18 configured to perform a filtering process on the reconstructed image, wherein the deblocking filtering unit 18 controls a filtering strength depending on a luminance signal level of the reconstructed image and the quantization parameter.