Digital Photography White Balance Correction for Mixed Lighting
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Solution Overview
Problem
Digital cameras struggle to maintain proper white balance in photographs taken with mixed lighting conditions, particularly when using a strobe light source that differs in color from ambient lighting, leading to discordant color appearances in images.
Innovation Solution
A system and method that involve loading source images, including a strobe image and an ambient image, to estimate pixel-level corrections and apply color correction, blending these images using a blend weight to generate a combined image that maintains proper white balance across regions illuminated by both sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a strobe light source with different color temperature is used to illuminate the scene, then the exposure and subject detail are improved, but the color consistency and white balance across different lighting regions deteriorate
Solution Approach 1:
The image is segmented into multiple regions based on illumination source identification. The processor divides the image data into strobe-illuminated regions and ambient-illuminated regions, allowing independent white balance processing for each region. This segmentation enables the system to apply different color correction strategies to different parts of the image, resolving the color inconsistency caused by mixed lighting sources.
Solution Approach 2:
The system applies local white balance correction to specific regions rather than uniform global correction. By identifying which regions are illuminated by the strobe versus ambient light, the processor applies region-specific gain adjustments to red, green, and blue channels. This local quality approach ensures that each region maintains its proper color balance according to its specific illumination conditions.
2Measurement precision
If conventional white balance compensation is applied to the entire image, then the color accuracy under ambient lighting is improved, but the color accuracy under strobe illumination deteriorates
Solution Approach 1:
The white balance correction is made dynamic and adaptive rather than static. The system continuously analyzes the image to identify illumination regions and adjusts white balance parameters accordingly. This dynamic approach allows the system to adapt to mixed lighting conditions by switching between different white balance strategies for different regions, rather than applying a fixed correction to the entire image.
Solution Approach 2:
The system introduces an intermediary processing stage between image capture and final output. A region identification module acts as an intermediary that analyzes illumination characteristics and generates region masks. These intermediary structures enable the subsequent white balance correction to be applied selectively, bridging the gap between the conflicting requirements of ambient and strobe illumination regions.
3Stability of the object's composition
If the strobe gain is reduced to match ambient lighting color, then the white balance under ambient lighting is improved, but the exposure and brightness under strobe illumination deteriorate
Solution Approach 1:
The image processing is segmented into separate channels for different illumination regions. By dividing the image data into strobe-illuminated and ambient-illuminated portions, the system can apply different gain values to each segment. This allows the strobe regions to maintain their higher brightness while ambient regions maintain proper white balance, eliminating the need to compromise either aspect.
Solution Approach 2:
The system dynamically changes the gain parameters for different regions based on illumination type. Rather than using fixed gain values, the processor adjusts red, green, and blue channel gains independently for strobe and ambient regions. This parameter change strategy allows optimal brightness preservation in strobe regions while maintaining color accuracy in ambient regions.
Data Source
AI summary
A system, method, and computer program product are provided for rendering a combined image. In use, two or more source images including at least one strobe image and at least one ambient image are loaded. A pixel-level correction is estimated for at least one of the two or more source images based on a pixel level correction function. At least one pixel of the two or more source images is color-corrected based on the pixel-level correction. A first blend weight associated with the two or more source images is initialized, and a first combined image from the two or more source images is rendered based on the color-correction and the first blend weight. Additional systems, methods, and computer program products are also presented.