Image Processing Device Subject Brightness Bracketing HDR Synthesis
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Solution Overview
Problem
Conventional image processing technologies face challenges in capturing high-quality images with high contrast brightness scenes, as they often result in overexposed or underexposed areas, and high dynamic range (HDR) images suffer from decreased contrast and unnatural brightness changes due to manual exposure adjustments and existing HDR techniques.
Innovation Solution
An image processing method and device that automatically retrieve and analyze images to determine subject brightness, use this as a reference for bracketing multiple exposures, synthesize HDR images, and optimize subject brightness to enhance image quality by adjusting the brightness of the subject in the HDR image when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a longer exposure setting is used to increase the image brightness of the subject area, then the subject brightness is improved, but the background area becomes overexposed
Solution Approach 1:
The image is divided into subject area and background area, with different exposure settings applied to each region. The system captures multiple images with different exposure values and selectively combines them, allowing the subject area to use longer exposure for adequate brightness while the background area uses shorter exposure to avoid overexposure.
Solution Approach 2:
Different exposure qualities are applied to different parts of the image. The subject area receives optimized exposure treatment (longer exposure for adequate brightness) while the background area receives different exposure treatment (shorter exposure to prevent overexposure), ensuring each region has the appropriate exposure quality for its specific requirements.
2Object-affected harmful factors
If a shorter exposure time is selected to avoid overexposure in the bright area, then the background overexposure is prevented, but the subject area becomes too dark due to underexposure
Solution Approach 1:
The image processing system segments the scene into subject and background regions, then applies different exposure strategies to each. The background area is protected from overexposure using shorter exposure settings, while the subject area is compensated through image synthesis techniques that restore adequate brightness.
Solution Approach 2:
The system applies localized exposure quality control where the background area receives protection from overexposure through shorter exposure settings, while the subject area receives enhanced brightness treatment through selective image synthesis and tone reproduction adjustments.
3Reliability
If conventional HDR technique is used to process multiple images with different exposure values, then the dynamic range is restored accurately, but the subject brightness is lowered and contrast decreases
Solution Approach 1:
The system applies different tone reproduction qualities to different regions. The background area undergoes conventional HDR tone reproduction to restore dynamic range, while the subject area is protected from excessive brightness reduction through selective processing, maintaining better brightness and contrast in the subject region.
Solution Approach 2:
The HDR processing is segmented into subject area processing and background area processing. The system captures multiple exposure images and synthesizes them differently for each region, preserving subject brightness and contrast while still achieving dynamic range restoration in the overall image.
4Adaptability or versatility
If manual exposure adjustment is performed for HDR image processing, then the exposure value can be customized, but the process becomes time consuming and prone to glow artifacts
Solution Approach 1:
The system performs automatic exposure value determination and image synthesis without requiring manual user input. The processor automatically analyzes the captured images, determines appropriate exposure values, and synthesizes the HDR image, eliminating the time-consuming manual adjustment process while maintaining adaptability to different scenes.
Solution Approach 2:
The manual mechanical adjustment process is replaced with automated computational processing. The system uses image processing algorithms and synthesis techniques to automatically determine optimal exposure values and combine images, replacing the manual slider adjustment mechanism with intelligent automated processing that is both faster and more consistent.
Data Source
AI summary
The disclosure provides an image processing method and an image processing device. The method includes: retrieving a first image of a specific scene, and capturing a first subject from the first image; determining a first brightness based on the first subject; using the first brightness as a reference value of a bracketing mechanism, and performing the bracketing mechanism to capture a plurality of second images of the specific scene; synthesizing the second images as a first high dynamic range image; capturing a second subject from the first high dynamic range image, wherein the second subject has a second brightness; when the second brightness is lower than the first brightness by a predetermined threshold, optimizing the second subject; synthesizing the optimized second subject with the first high dynamic range image as a second high dynamic range image.