Virtual Lighting Adjustment via Regression Analysis
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Solution Overview
Problem
Users face challenges in capturing professional-quality images without the expertise or cost of hiring a professional photographer, as personal devices and standalone cameras lack advanced features and user experience.
Innovation Solution
A system and method for providing virtual lighting adjustments to image data in real-time using a computing device, which applies pre-generated models to modify pixel characteristics such as brightness, hue, and saturation, allowing users to enhance images and videos with professional-looking lighting effects without external assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If professional photography equipment and services are used, then image quality is improved, but cost and convenience deteriorate
Solution Approach 1:
The patent creates virtual lightmaps that copy and simulate professional lighting effects through software processing. Instead of requiring physical professional equipment, the system generates digital representations of professional lighting scenarios that can be applied to photos taken with consumer devices, thereby achieving professional-quality results without the associated costs and convenience issues
Solution Approach 2:
The patent replaces mechanical/physical lighting systems with computational algorithms. Rather than using actual professional lighting equipment and photographer expertise, the system uses image processing algorithms to automatically analyze and adjust lighting in photos, substituting computational methods for physical systems and human expertise
2Manufacturing precision
If professional photography equipment is used, then image quality is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal software solution that can be applied to images from various consumer devices. The virtual lighting adjustment system is device-agnostic and can process photos from different camera types, making professional-quality enhancement accessible across multiple platforms without requiring specialized equipment for each device type
Solution Approach 2:
The system uses pre-generated virtual lightmaps that serve as templates for professional lighting effects. These lightmaps are created once and can be applied repeatedly to numerous images, eliminating the need for complex equipment while maintaining consistent professional-quality results across different photos and devices
3Speed
If real-time lighting adjustments are applied, then processing speed is improved, but computational complexity increases
Solution Approach 1:
The patent pre-generates virtual lightmaps during an offline training phase, where complex computational work is performed in advance. The system creates comprehensive lighting adjustment maps that capture various lighting scenarios, then stores these for rapid application during real-time photo processing, thereby separating heavy computation from time-critical operations
Solution Approach 2:
The patent divides the lighting adjustment process into distinct components: color channel separation, luminance calculation, and virtual lightmap application. By segmenting the complex processing into manageable stages with pre-computed intermediate results, the system reduces real-time computational burden while maintaining processing quality and speed
Data Source
AI summary
Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for providing virtual lighting adjustments to image data. A number of source images may be generated to individually depict solid colors of a color space (e.g., RGB color space). Virtual lighting adjustments associated with a virtual lighting mode may be applied to each source image to generate a corresponding target image. The source images and the target images may be utilized to train a model to identify pixel modifications to be applied to image data. The modifications may be associated with a virtual lighting mode. Subsequently, a user may obtain image data (e.g., an image or video) select a virtual lighting mode via an image data processing application. The previously trained model may be utilized to modify the image to apply the virtual lighting effects associated with the selected virtual lighting mode.