Structure-Preserving Filter for Interactive Image Noise Separation
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Solution Overview
Problem
Existing image denoising methods often smooth out image structures and fail to adequately remove noise from certain regions, resulting in artifacts and suboptimal quality, especially in low-light conditions where high ISO settings increase noise levels.
Innovation Solution
An interactive system employing a structure-preserving filter that allows users to refine image-noise separation results through a brush-based interface, enabling the distinction between random noise and image structures, and iteratively improving the separation of noise from image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If automated denoising algorithms are used to remove noise, then noise reduction is achieved, but image structures are smoothed out and quality deteriorates
Solution Approach 1:
The patent segments the image into multiple regions based on edge detection and structural analysis. Different denoising strategies are applied to different segments: aggressive denoising in smooth regions and conservative denoising in edge-rich regions. This segmentation allows simultaneous noise reduction and structure preservation.
Solution Approach 2:
The patent applies local quality by adjusting denoising parameters based on regional characteristics. In regions with strong edges and structures, the algorithm preserves details while removing noise. In smooth regions, it applies stronger denoising. This spatially adaptive approach resolves the contradiction between noise removal and structure preservation.
2Productivity
If fully automatic noise removal is applied, then processing speed is improved, but user control is lost and artifacts appear
Solution Approach 1:
The patent implements dynamic user interaction where the denoising process adapts based on user feedback. The system provides preliminary automatic denoising results and allows users to adjust parameters or correct artifacts interactively. This dynamic approach maintains productivity while restoring user control when needed.
Solution Approach 2:
The patent incorporates feedback mechanisms where users can evaluate denoising results and provide corrections. The system uses this feedback to refine the denoising process, allowing users to control specific regions or parameters. This feedback loop resolves the contradiction by maintaining automatic processing speed while enabling user control when artifacts appear.
3Illumination intensity
If high ISO settings are used in low-light conditions, then image brightness is improved, but noise levels increase significantly
Solution Approach 1:
The patent converts the harmful noise introduced by high ISO settings into a beneficial effect by using noise-aware denoising algorithms. Instead of simply removing all noise, the system identifies and preserves useful structural information while removing only the harmful random noise components. This approach leverages the presence of noise to guide the denoising process, achieving both brightness preservation and noise reduction.
Data Source
AI summary
An interactive system for separating image information from noise information in noisy input images may include a structure-preserving filter capable of separating high- and low-frequency image structures from random noise. The system may access data representing an initially denoised image and a corresponding initial noise layer, apply the structure-preserving filter to the noise layer to extract image structure, and combine the extracted structure with the initially denoised image to produce a refined image, restoring structure incorrectly removed from an image by a previous denoising operation. The system may provide brush tools to identify regions on which to apply the filter and mechanisms to specify filter parameter values. The filter may be applied iteratively to improve results, and may be employed in noise-consistent image editing tasks to preserve original image noise. The filter may be implemented by program instructions stored on a computer readable medium and executable by CPUs and/or GPUs.