Image Frame CRC Detection for SDI Pixel Loss Indication
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Solution Overview
Problem
During the transmission of high-resolution images through serial digital interfaces (SDIs), pixel data loss can occur due to incorrect connections or transmission errors, affecting the display quality of 4K and 8K images, as these losses can be scattered and not immediately apparent, leading to poor image quality or integrity issues.
Innovation Solution
A method is introduced to process image frames by determining pixel data loss using cyclic redundancy check (CRC) codes and threshold ratios, and applying preset replacement data to affected pixels or pixel arrays, which can indicate faulty links or connections, thereby reminding users to troubleshoot and maintain the SDI transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pixel data is transmitted through SDI interfaces for high-resolution images, then image transmission capability is improved, but pixel data loss occurs due to incorrect connections or transmission errors
Solution Approach 1:
The patent applies preliminary action by checking CRC codes of pixel data before displaying the image. The system performs data integrity verification in advance, identifying lost or erroneous pixel data before it reaches the display output, allowing for corrective measures to be taken proactively rather than reactively after display errors occur.
Solution Approach 2:
The patent implements feedback mechanisms by monitoring pixel data transmission through CRC verification and providing visual feedback through mark display. When data loss is detected, the system generates visual indicators (marks) that provide feedback about the location and nature of transmission errors, enabling users to identify and correct connection or transmission issues.
2Reliability
If pixel data loss is detected and marked, then data integrity is improved, but device complexity increases due to additional processing steps
Solution Approach 1:
The patent applies segmentation by dividing the image into multiple pixel arrays and assigning different marks to different arrays. This segmentation allows the system to identify which specific portion of the image has data loss without needing to process or mark the entire image, reducing the overall complexity of the error handling process while maintaining data integrity.
Solution Approach 2:
The patent implements local quality by applying different visual marks to different pixel arrays based on their specific data loss conditions. Instead of treating the entire image uniformly, the system applies localized corrections and markings only to the affected pixel arrays, optimizing processing efficiency while ensuring data integrity in each local region.
3Reliability
If replacement data is used for lost pixels, then image completeness is improved, but visual quality deteriorates due to visible artifacts
Solution Approach 1:
The patent applies color changes by using visually distinct marks to indicate pixel arrays with data loss. These marks create intentional visual indicators that allow users to immediately identify areas requiring attention. The color or visual property changes serve as a diagnostic tool rather than attempting to perfectly reconstruct the original image content, balancing completeness with visual quality.
Data Source
AI summary
A method for processing an image frame includes: obtaining an image frame to be displayed; determining whether pixel data in the image frame to be displayed is lost; and using preset replacement data as data of target pixels in the image frame to be displayed, in response to determining that the pixel data in the image frame to be displayed is lost.