Image Lighting Rendering Using Depth and Tangent Features
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Solution Overview
Problem
Existing image processing technologies provide limited lighting rendering effects due to reliance on single normal information, lacking depth and tangent feature information for richer lighting effects.
Innovation Solution
Acquire and utilize depth and tangent feature information of a target object in an image processing method to perform lighting rendering, enhancing lighting effects with varied angles, intensities, and distributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If only normal information is used for lighting rendering, then the processing complexity is low, but the lighting rendering effect is single and limited
Solution Approach 1:
The patent segments the feature information extraction into distinct components: normal information, depth information, and tangent information. Each component is extracted and processed separately using specific neural network modules, allowing the system to handle complex multi-dimensional feature data while maintaining manageable processing complexity through modular architecture.
Solution Approach 2:
The patent transitions from two-dimensional normal information to three-dimensional feature space by incorporating depth information and tangent information. This dimensional expansion enables richer lighting rendering effects by adding spatial and directional dimensions to the traditional normal map approach, allowing for more realistic and varied lighting simulations.
2Adaptability or versatility
If multiple feature information (depth and tangent) are acquired and used, then the lighting rendering effect is enriched, but the information processing complexity increases
Solution Approach 1:
The patent merges multiple feature information types (normal, depth, and tangent) into a unified lighting rendering process. The neural network integrates these different feature dimensions together to produce comprehensive lighting effects, ensuring that no single feature component is lost while achieving enriched rendering outcomes through combined feature processing.
3Measurement precision
If comprehensive feature information is processed, then the lighting simulation accuracy is improved, but the computational requirements increase
Solution Approach 1:
The patent performs preliminary feature extraction and organization before the main lighting rendering computation. By pre-processing the image to extract normal, depth, and tangent information in advance and organizing them into structured feature maps, the system reduces the computational burden during the actual lighting simulation phase, improving efficiency while maintaining high accuracy.
Data Source
AI summary
Embodiments of the present disclosure provide an image processing method and apparatus, an electronic device, and a readable storage medium. The method includes: acquiring a to-be-processed image, where the to-be-processed image includes a target object; acquiring, by adopting a feature model, normal feature information and target feature information of the target object, where the target feature information includes: depth feature information and/or tangent feature information; performing, based on the normal feature information and the target feature information, a lighting rendering on the target object in the to-be-processed image to obtain a lighting-rendered-image; and outputting the lighting-rendered-image. Compared with the prior art, in the present disclosure, a terminal device may perform the lighting rendering on the target object based on richer feature information of the target object, which can enrich a lighting rendering effect.