Image Signal Processing Subject Recognition Brightness Control
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Solution Overview
Problem
Existing image signal processing systems struggle to maintain adequate brightness and gradation in images captured in environments with large brightness differences, leading to discontinuous subject brightness due to block-based contrast correction.
Innovation Solution
An image signal processing system that recognizes specific subjects and performs image processing using luminance distribution information to expand the gradation of desired subjects, allowing for improved visibility by controlling the input-output characteristic of each small area, particularly around the subject of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If block-based contrast correction is performed to improve local brightness differentiation, then local brightness correction is achieved, but subject brightness becomes discontinuous at block boundaries
Solution Approach 1:
The image is divided into multiple blocks, and contrast correction is performed independently for each block based on local luminance statistics. This allows local brightness differentiation while maintaining overall image coherence through consistent processing across all blocks.
Solution Approach 2:
Different contrast correction parameters are applied to different blocks based on their local luminance characteristics. Each block's correction is tailored to its specific luminance distribution, achieving local optimization without uniform processing across the entire image.
2Illumination intensity
If AE (Auto Exposure) control is used to provide adequate brightness for the entire image, then overall brightness is improved, but images with large brightness differences cannot maintain adequate gradation
Solution Approach 1:
The image processing is segmented into global AE control and local block-based contrast correction. The AE control handles overall brightness, while the block-based processing handles local gradation, allowing both functions to operate effectively without interfering with each other.
Solution Approach 2:
Local contrast correction is applied to each block based on its specific luminance distribution, preserving gradation accuracy in regions with large brightness differences while the global AE control maintains adequate overall brightness.
3Measurement precision
If subject recognition is added to perform targeted image processing, then visibility of desired subjects is improved, but device complexity increases
Solution Approach 1:
Subject recognition and detection are performed before the main image processing steps. This preliminary identification allows subsequent contrast correction and brightness adjustment to be targeted at specific subjects, improving visibility without requiring complex real-time adjustments.
Solution Approach 2:
The block-based contrast correction mechanism serves multiple functions: it corrects local brightness, preserves subject continuity, and when combined with subject recognition, selectively enhances desired subjects. This multi-functionality reduces the need for separate dedicated systems.
Data Source
AI summary
An image signal processing system according to the present invention has a function to perform image quality control in photographing a subject having a large difference in brightness in the surrounding environment so that the entire photographed image, in particular a subject which a user desires to view, has an adequate brightness and an adequate gradation. Specifically, this image signal processing system comprises: a video input unit, a video signal processing unit for performing signal processing on a signal output from the video input unit, and generating a video signal; an input-output characteristic control unit for controlling a characteristic of the video signal which the video signal processing unit generates; and a subject recognition unit for performing image processing on the video signal which the video signal processing unit generates, and recognizing and detecting subject information.