Image Defocusing Estimation Using PSF and Adjustable Thresholds
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Solution Overview
Problem
Existing image evaluation methods for digital cameras and smartphones fail to account for user preferences beyond defocusing, leading to incorrect image selection based on absolute criteria rather than intended composition or facial expression, and require manual visual inspection for defocusing assessment.
Innovation Solution
An image processing apparatus that sets an estimation area, estimates defocusing using a point spread function (PSF), and allows users to adjust a threshold for determining defocusing through a display interface, enabling relative evaluation of images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated PSF estimation is used to evaluate defocusing, then productivity is improved, but measurement precision deteriorates because it only evaluates absolute defocusing degree without considering user preferences
Solution Approach 1:
The image is divided into multiple patches, and defocusing evaluation is performed separately for each patch. This allows the system to evaluate different regions with different criteria, combining automated efficiency with user-preference-based accuracy by allowing selective focus on important regions.
Solution Approach 2:
The system changes the evaluation parameter from absolute defocusing degree to relative defocusing degree within patches. By evaluating defocusing relative to each patch's characteristics rather than using a uniform absolute threshold, the system maintains automated processing while improving evaluation accuracy to match user preferences.
2Measurement precision
If the entire image is used for defocusing estimation, then measurement precision is improved, but device complexity increases due to larger processing area
Solution Approach 1:
The image is divided into multiple smaller patches for independent defocusing estimation. This segmentation reduces the computational complexity of processing the entire image at once while maintaining measurement precision through comprehensive coverage of all regions, including important objects and backgrounds.
Solution Approach 2:
The system performs defocusing estimation on selected patches rather than uniformly processing the entire image. By selectively evaluating only relevant patches (those containing important objects or regions of interest), the system achieves sufficient measurement precision without the full computational burden of processing every pixel.
Data Source
AI summary
An apparatus includes at least one memory configured to store instructions, and at least one processor in communication with the at least one memory and configured to execute the instructions to set an estimation area to acquired image data, execute calculation for estimating a degree of defocusing of an image in the estimation area, determine defocusing of the image data based on the estimated degree of defocusing, and display information which allows a user to adjust a threshold for determining defocusing on a display.