Dynamic Range Compensation Noise Reduction
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Solution Overview
Problem
Existing noise reduction techniques in digital cameras enhance noise as well as details during dynamic range compensation, leading to graininess and speckle in compensated regions, and are inadequate for high-ISO images with high noise levels.
Innovation Solution
Concurrent and interactive pixel-by-pixel processing of dynamic range compensation and noise reduction, where the noise reduction factor is responsive to the gain factor determined by dynamic range compensation, ensuring uniform noise variance across the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If dynamic range compensation is applied to enhance image details in dark areas, then image contrast and detail visibility are improved, but noise levels are amplified and become non-uniform across the image
Solution Approach 1:
The patent applies preliminary noise reduction processing before dynamic range compensation to counteract the noise amplification that will occur during DRC. By reducing noise in advance and then applying DRC with appropriate gain factors, the system achieves enhanced image contrast while preventing excessive noise amplification in the final output image.
Solution Approach 2:
The patent implements spatially varying noise reduction and DRC parameters, where different regions of the image receive different processing intensities. In uniform regions, stronger noise reduction is applied, while in regions with edges or textures, the processing is adjusted to preserve detail. This local adaptation allows contrast enhancement without uniform noise amplification across the entire image.
2Object-generated harmful factors
If noise reduction is applied to remove noise from the image, then noise levels are reduced, but image detail and texture are also removed
Solution Approach 1:
The patent employs local quality assessment to differentiate between noise and image details at each pixel location. By analyzing local image characteristics such as gradient magnitude and texture patterns, the system applies stronger noise reduction in uniform regions while preserving edges and fine details in regions with significant variations. This selective approach maintains image detail while reducing noise.
Solution Approach 2:
The patent uses dynamic parameter adjustment where noise reduction strength varies based on local image content. The processing parameters are adapted in real-time according to the detected image features, allowing the system to dynamically balance between noise removal and detail preservation across different regions of the image.
3Device complexity
If sequential processing of noise reduction followed by dynamic range compensation is used, then processing simplicity is maintained, but noise variance becomes non-uniform and graininess increases
Solution Approach 1:
The patent merges noise reduction and dynamic range compensation into a unified processing framework where both operations are performed with coordinated parameters. The noise reduction step uses gain factors that are responsive to the DRC operation, and the DRC gain is applied to the noise-reduced image. This combined approach ensures that noise variance remains uniform across the image while maintaining processing simplicity.
4Productivity
If high-ISO images are processed with conventional noise reduction, then processing speed is maintained, but noise levels remain high and image quality deteriorates
Solution Approach 1:
The patent applies preliminary noise reduction processing to high-ISO images before dynamic range compensation, using optimized algorithms that efficiently reduce noise while preserving details. This preliminary action prepares the image for subsequent DRC operation, ensuring that even high-ISO images with initially high noise levels achieve acceptable quality while maintaining processing speed through efficient implementation.
Data Source
AI summary
Methods and corresponding apparatus are presented that perform dynamic range compensation (DRC) and noise reduction (NR) together on a pixel-by-pixel basis, adjusting the noise reduction parameters in response to the dynamic range compensation decisions. By such a modification of image noise reduction parameters based on the dynamic range compensation gain or, more generally, other such factors, these techniques make it possible to perform DRC on noisy images, achieving an image with low and uniform noise levels.