Image Processing Apparatus Dynamic Range Enhancement Noise Removal
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image processing technologies face challenges in effectively improving the dynamic range and removing noise from input images, particularly in low-light environments, leading to difficulties in distinguishing objects and backgrounds.
Innovation Solution
An image processing method that calculates a luminance component, estimates an illuminance component, and applies a gamma value to enhance the dynamic range, while also using a non-local means algorithm to remove noise based on dissimilarity values between reference and target patches, thereby generating an improved image with enhanced dynamic range and reduced noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise removal technology is applied to improve image quality, then noise is reduced, but dynamic range is narrowed
Solution Approach 1:
The patent segments the image processing into separate modules: one for noise removal and another for contrast enhancement. The noise removal module processes the image to reduce noise, while the contrast enhancement module separately adjusts the dynamic range. This segmentation allows each module to optimize its function without compromising the other, resolving the contradiction between noise removal and dynamic range preservation.
Solution Approach 2:
The patent introduces an intermediary processing stage that combines noise removal and contrast enhancement. The intermediary module receives the noise-removed image and applies contrast enhancement algorithms to restore and expand the dynamic range, acting as a mediator between noise removal and dynamic range preservation to achieve both goals simultaneously.
2Illumination intensity
If contrast enhancement technology is applied to improve dynamic range, then dynamic range is improved, but noise is amplified
Solution Approach 1:
The patent applies preliminary action by performing noise removal before contrast enhancement. The noise removal module processes the input image first to reduce noise, and then the contrast enhancement module operates on the cleaned image. This preliminary noise removal prevents noise amplification during subsequent contrast enhancement, resolving the contradiction between improving dynamic range and avoiding noise amplification.
Solution Approach 2:
The patent maintains continuity of useful action by implementing a sequential processing pipeline where noise removal and contrast enhancement are performed in continuous stages. The output of the noise removal module serves as the input to the contrast enhancement module, ensuring that the useful actions of both processes continue without interruption and work together to achieve both noise reduction and dynamic range improvement.
3Measurement precision
If image processing is performed to improve quality, then image clarity is improved, but processing time is increased
Solution Approach 1:
The patent segments the image processing into separate functional modules: noise removal module and contrast enhancement module. Each module can be optimized independently for computational efficiency, allowing parallel processing or selective application based on image content. This segmentation reduces overall processing time while maintaining image clarity by avoiding redundant computations.
Solution Approach 2:
The patent applies partial action by selectively applying processing algorithms only to regions or areas that require attention, rather than processing the entire image uniformly. The noise removal and contrast enhancement operations are applied partially to areas with high noise or low contrast, reducing processing time while maintaining image clarity in critical regions.
Data Source
AI summary
An image processing method includes receiving an image, calculating a luminance component of the received image, estimating an illuminance component of the image by using the luminance component, calculating a gamma value, based on the luminance component and the illuminance component, and calculating the luminance component with an improved dynamic range using a conversion ratio based on the gamma value.