Block-Based Image Filtering for Artifact Reduction
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Solution Overview
Problem
Existing methods for reducing rendering artifacts on display devices are inefficient, particularly on devices with slower GPUs, as they often require preprocessing of images or uniform blurring, which can cause delays and are impractical for all devices.
Innovation Solution
Applying a high-frequency or edge-detection filter to divide images into blocks and calculate density values, allowing for varying degrees of blur only on blocks with high artifact levels, thereby reducing artifacts while maintaining image detail in other areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an image is preprocessed to display correctly on the display device, then rendering artifacts are reduced, but it is impractical to preprocess an image to correctly display on all of the various display devices
Solution Approach 1:
The patent changes the parameter of image processing from uniform preprocessing to selective block-based processing. By dividing the image into blocks and applying different processing parameters (blur vs. no blur) to different blocks based on artifact detection, the system adapts to various display devices without requiring separate preprocessing for each device type.
2Reliability
If a display device with a fast GPU modifies the displayed image to reduce rendering artifacts, then artifact reduction is effective, but mobile devices with slower GPUs cannot modify the image quickly, causing a delay in rendering
Solution Approach 1:
The patent segments the image processing task into block-level operations. By dividing the image into smaller blocks and processing only those blocks that contain artifacts, the computational load is significantly reduced compared to processing the entire image, enabling faster rendering on mobile devices with slower GPUs.
Solution Approach 2:
The patent applies partial action by processing only the necessary portions of the image (blocks with artifacts) rather than the entire image. This selective processing reduces the overall computational burden and rendering time while still achieving effective artifact reduction where needed.
3Reliability
If uniform blurring is applied to the entire image to reduce artifacts, then artifacts are reduced, but image detail is lost in areas without artifacts
Solution Approach 1:
The patent applies local quality by making different parts of the image have different processing characteristics. Blocks detected to contain artifacts are blurred, while blocks without artifacts retain their original detail. This localized approach ensures that image quality is preserved in areas that do not require artifact reduction.
Data Source
AI summary
Image filter values can be obtained by applying a high-frequency or edge-detection image filter to an image to extract a level of image detail. The image can be divided into blocks of a predetermined size and the image filter values of the pixels in a block can be used to obtain a density value associated with the level of image detail for the block. For blocks where the density value exceeds a threshold amount, a degree of blur may be applied based on the density value. Thus, the image can be rendered so that only some of the blocks of the image are blurred while other blocks do not have blur applied.