Composite Image Encoding With Rendering-Intent Metadata
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image encoding and decoding technologies fail to transmit the original captured image data accurately, leading to lossy operations due to non-linear clipping and unknown algorithms, and lack backwards compatibility for multiple rendering intents.
Innovation Solution
Encoding and decoding methods that transmit metadata alongside image data to allow inversion of adjustments, enabling multiple rendering intents, including the original captured 'reality' image or a modified 'pleasing' image, while maintaining compatibility with different display devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple images corresponding to different user intents are displayed together, then user engagement and information delivery are improved, but image selection complexity and processing time increase
Solution Approach 1:
The patent segments the image selection process by dividing images into different intent categories (informational, navigational, transactional, etc.). Each category is processed and selected independently based on its specific criteria, rather than evaluating all images uniformly. This segmentation reduces the complexity of the overall selection process while maintaining high adaptability to different user needs.
Solution Approach 2:
The system performs preliminary classification of images into intent categories before the actual selection process. By pre-organizing images according to their intended purpose and user intent type, the system reduces the computational complexity during real-time operation, making the selection process more efficient while maintaining versatility.
2Adaptability or versatility
If multiple images corresponding to different user intents are displayed together, then user engagement and information delivery are improved, but rendering time increases
Solution Approach 1:
The patent implements preliminary processing of images including pre-generation of thumbnails, pre-computation of metadata, and pre-classification into intent categories. This preliminary action ensures that when images need to be rendered for display, the processing time is minimized since the heavy lifting has already been done in advance.
Solution Approach 2:
The rendering process is segmented into parallel operations where different image categories are processed simultaneously based on their priority levels. High-priority images (such as primary search results) are rendered first, while lower-priority images are processed in parallel or deferred, reducing the overall perceived rendering time while maintaining comprehensive information delivery.
3Ease of operation
If image thumbnails are generated for multiple images, then user interface quality and user experience are improved, but processing time and computational resources increase
Solution Approach 1:
The system generates image thumbnails periodically or on-demand rather than continuously for all images. Thumbnails are generated in advance for frequently accessed images and updated periodically, while less frequently accessed images have their thumbnails generated only when needed. This periodic action significantly reduces processing time while maintaining high user experience quality.
Solution Approach 2:
The patent applies different thumbnail generation qualities and resolutions based on the specific image category and its intended use. High-quality thumbnails are generated for primary display positions, while lower-quality thumbnails suffice for secondary positions or preview modes. This local quality approach reduces overall processing time and computational resources while maintaining excellent user experience where it matters most.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Techniques for multiple-intent composite image encoding and rendering are disclosed. The techniques can include obtaining a set of constituent images for a composite image, determining a common rendering intent to be applied to the set of constituent images, adjusting one or more of the set of constituent images according to the common rendering intent, resulting in an adjusted set of constituent images, creating the composite image based on the adjusted set of constituent images, generating metadata characterizing the common rendering intent, and encoding the composite image and the metadata to create an encoded multiple-intent composite image.