Dual Camera Image Combination with Quality Selection
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Solution Overview
Problem
Current dual camera portable terminals face challenges in ensuring the quality of combined images due to size limitations of sub-images and hand trembling, leading to unsatisfactory combined images.
Innovation Solution
A method that selects and combines images based on predetermined classification references such as blur, facial expression, and shooting composition, ensuring that only high-quality images are used for the final combined image, and adjusts brightness or tone differences between front and rear images if they exceed a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are combined from dual cameras in PIP form, then user can simultaneously identify two images, but sub image quality cannot be properly identified due to size limitation
Solution Approach 1:
The system performs preliminary selection of effective images from multiple captured frames before combining them. By pre-selecting images that meet quality criteria (sharpness, exposure, composition) and storing them in a buffer, the system ensures that only high-quality images are combined, addressing the quality identification issue before the actual combination occurs.
2Adaptability or versatility
If images are combined from dual cameras, then diverse image combining applications are possible, but combined image quality deteriorates due to hand trembling
Solution Approach 1:
The system performs preliminary stabilization by selecting the sharpest image from multiple captured frames and using it as a reference. This pre-selection process compensates for hand trembling effects before image combination, ensuring that the reference image is stable and of high quality.
Solution Approach 2:
The system uses sharpness evaluation metrics to assess image quality and provides feedback for selecting the best image. By continuously evaluating image quality parameters (sharpness, exposure, focus) and using this feedback to select effective images, the system ensures reliable combined image quality even under hand trembling conditions.
3Reliability
If multiple images are captured successively, then effective images can be selected based on classification references, but image selection complexity increases
Solution Approach 1:
The system segments the image selection process into distinct evaluation stages: sharpness evaluation, exposure evaluation, and composition evaluation. Each stage independently assesses specific image parameters, and the results are combined to determine the final effective image. This segmentation simplifies the overall selection complexity by breaking it down into manageable, independent evaluation modules.
Data Source
AI summary
An image combining method in an electronic device having a plurality of cameras. In response to a photographing signal, images successively photographed through at least a first camera are successively stored. A first image is selected from the successively photographed images which satisfies a predetermined classification reference, such as a degree of blurring, a facial expression, and/or a shooting composition. A second image is captured through a second camera; and the first and second images are then combined. The combined image may be a picture-in-picture (PIP) type combination image. The first and second cameras may be front and rear cameras of a portable terminal, or vice versa. The successive image capture and selection technique may also be applied to the second camera.