Camera Image Haze Correction With Luminance Shift and Contrast Stretching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electronic devices often capture images with distorted quality due to inherent factors such as sensors, displays, or lenses, leading to issues like haze and luminance distortions that affect image clarity and representation.
Innovation Solution
The electronic device employs a method to enhance image quality by adjusting luminance values through luminance shift and contrast stretching, applying weights to different regions of the image, and incorporating dithering to reduce artifacts, while also transmitting relevant parameters to external devices for further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If luminance values are adjusted through luminance shift and contrast stretching to correct haze and luminance distortions, then image clarity and representation accuracy are improved, but device complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by performing luminance shift and contrast stretching operations in advance during the image processing pipeline. The processor pre-calculates and applies correction factors based on captured luminance values before final image rendering, thereby improving image clarity while managing processing complexity through advance preparation rather than real-time computation.
2Manufacturing precision
If dithering is applied to reduce bending artifacts in luminance adjustment, then image quality is improved, but processing time and computational load increase
Solution Approach 1:
The patent applies partial action by implementing dithering selectively rather than uniformly across the entire image. The processor identifies regions with bending artifacts and applies dithering only to those specific areas, thereby improving image quality where needed while minimizing unnecessary processing time and computational load in regions that do not require artifact reduction.
3Measurement precision
If weight ratios are adjusted to apply different processing strengths to different image regions, then image representation accuracy is improved, but ease of operation decreases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting weight ratios based on captured luminance values and detected haze levels. The processor automatically modifies processing parameters such as luminance shift magnitude and contrast stretching intensity according to the specific image conditions, thereby improving image representation accuracy while reducing the burden on users to manually tune complex parameters.
Data Source
AI summary
An electronic device may be provided. The electronic device may include a camera; a display; at least one processor; and memory storing instructions. The instructions, when executed by the at least one processor, cause the electronic device to: obtain a first image having first luminance values via the camera; obtain a haze level in accordance with a designated lower ratio of the first luminance values of the first image; and display, through the display, a second image having final luminance values based on identifying that the haze level is equal to or greater than a threshold. The final luminance values are obtained based on: luminance shift for converting the first luminance values in accordance with a difference between a central luminance level of the first luminance values and a target luminance level, and contrast stretching for scaling an interval between luminance levels from the target luminance level.