Digital Camera Pixel Value Recalculation for Clipped Pixels
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Solution Overview
Problem
Digital cameras face issues with clipped pixels due to saturation in bright scenes, leading to loss of brightness range and unrealistic image replication, especially caused by overexposure and glare, resulting in many pixel values being maximized at 255.
Innovation Solution
The digital camera employs a method to determine and adjust exposure settings, such as changing exposure time and aperture, to recalibrate pixel values, using mathematical functions or lookup tables, to reduce the number of clipped pixels and improve image realism by altering the charge accumulation based on new settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If exposure time is increased to capture more light in bright scenes, then image brightness is improved, but pixel saturation increases causing clipped pixels
Solution Approach 1:
The system performs preliminary actions by capturing multiple images at different exposure times before final processing. This allows the system to pre-identify which pixels are likely to be clipped and prepare correction data in advance, enabling better brightness range preservation without requiring a single perfectly exposed image.
Solution Approach 2:
The system changes the exposure time parameter across multiple captures and uses mathematical functions to recalculate pixel values. By varying this parameter and applying transformation functions, the system can recover brightness information that would otherwise be lost in saturated pixels, converting clipped pixels into accurate brightness representations.
2Loss of information
If exposure time is decreased to prevent pixel saturation, then clipped pixels are reduced, but image becomes underexposed and dark
Solution Approach 1:
The system captures multiple images at different exposure levels as a preliminary step, ensuring that at least some images will have adequate exposure even if others are overexposed. This preliminary multi-exposure approach allows later selection or combination of properly exposed pixels while avoiding the need to choose a single exposure time that might be suboptimal.
Solution Approach 2:
By changing the exposure time parameter across multiple captures and using mathematical transformations, the system can compensate for underexposure in individual images. The recalculation function adjusts pixel values based on the relationship between different exposure times, recovering brightness information that would otherwise be lost in underexposed images.
3Reliability
If aperture is changed to adjust light intake, then exposure control is improved, but depth of field changes affecting image quality
Solution Approach 1:
The system segments the image into different regions based on their brightness characteristics and exposure status. By analyzing which pixels are clipped, dark, or properly exposed, the system can apply different processing strategies to different segments, maintaining depth of field while improving overall exposure control through selective pixel value adjustment.
Solution Approach 2:
The system uses mathematical functions to recalculate pixel values based on exposure time changes, effectively changing the exposure parameter without physically changing the aperture. This allows exposure control improvement while maintaining the original aperture setting and its associated depth of field characteristics.
4Measurement precision
If multiple images at different exposure times are captured and processed, then pixel value accuracy is improved, but processing time and complexity increase
Solution Approach 1:
The system applies different processing quality to different regions of the image based on their exposure status. Rather than uniformly processing all pixels, it identifies clipped and dark regions and applies corrective processing only to those areas, reducing overall processing complexity while maintaining high pixel value accuracy where needed.
Solution Approach 2:
The system uses mathematical functions and lookup tables to efficiently recalculate pixel values based on exposure time relationships. These pre-computed functions transform the complex multi-exposure processing into simpler mathematical operations, reducing processing complexity while maintaining the precision benefits of multi-exposure capture.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows users to correct image brightness issues by identifying and adjusting for clipped and dark pixels, enhancing the dynamic range and realism of captured images by preventing saturation and maintaining accurate light intensity representation.
Implementation Method 1
Light from the scene is focused onto the pixels, causing each pixel to accumulate a charge
Data Source
AI summary
Methods of calculating pixel values representative of a scene are disclosed herein. One embodiment of the method comprises focusing light representative of the scene onto a photosensor for a period of time using at least one exposure setting, wherein the photosensor has a plurality of pixels. Numeric values corresponding to the intensity of light received by each of the pixels during the period are generated. At least one exposure setting is changed and pixel values are generated by the photosensor based on the changed at least one exposure setting are calculated. The number of calculated pixel values that are greater than a first preselected value are then determined.