Feature-Based Autofocus Using Weight Maps for Limited Texture
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Solution Overview
Problem
Existing autofocus methods often fail to achieve optimal focus quality, especially in images with limited texture or obstructed features, leading to poor focus performance.
Innovation Solution
A feature-based autofocus method that determines a set of features in an image, generates a feature weight map, and estimates the direction of a target feature to calculate a focus position, improving focus quality by weighting target features based on their strength and location within the feature region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional autofocus methods are used, then the autofocus procedure can be performed, but the focus quality is poor in images with limited texture or obstructed features
Solution Approach 1:
The patent applies local quality by generating a feature weight map that assigns different weights to different regions of the image based on the presence and strength of features. Instead of uniform autofocus processing, the system identifies specific feature regions (such as facial features) and concentrates autofocus effort on those regions, allowing high-quality focus where features exist while accepting lower requirements in featureless regions.
Solution Approach 2:
The patent segments the image into feature regions and non-feature regions by detecting and weighting specific features. The autofocus procedure is then applied differently to these segments - with enhanced attention to feature regions containing detected features, and standard processing to other areas. This segmentation allows the system to adapt to images with limited texture by focusing computational resources on the most important regions.
2Measurement precision
If feature-based autofocus is implemented, then focus quality improves, but device complexity increases
Solution Approach 1:
The patent implements partial action by applying the computationally intensive feature detection and weighting process only to regions of the image where features are present, rather than processing the entire image uniformly. The system performs feature detection, generates weight maps only for feature regions, and applies autofocus enhancement selectively. This approach achieves improved focus quality while reducing overall processor utilization compared to applying full feature-based processing to the entire image.
3Measurement precision
If feature detection and weighting is performed, then autofocus accuracy improves, but power consumption increases
Solution Approach 1:
The patent reduces power consumption by applying feature detection and weighting operations only to local regions of the image where features are detected, rather than processing the entire image. The feature weight map is generated selectively for feature regions, and autofocus adjustments are applied locally. This localized approach maintains high autofocus accuracy for feature-containing regions while significantly reducing the computational energy required compared to global processing.
Data Source
AI summary
Methods, systems, and devices for feature-based image autofocus are described. A device may perform an autofocus procedure that includes determining a set of features based on determining a feature region associated with an image. The device may generate a feature weight map based on the set of features and estimate a direction of a target feature in the feature region. The device may generate a direction weight map that corresponds to the feature region. The device may determine a focus position of the image based on the generated feature weight map and the estimated direction of the target feature and perform an autofocus operation on the determined focus position of the image. The device may calculate a focus value based on the feature weight map, and the focus position of the image may be based on the focus value.