3D Film Noise Modulation via Depth-Dependent Spatial Resolution
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Solution Overview
Problem
In 3D imaging systems, the noise characteristics of left and right cameras often mismatch, leading to perceptually incorrect noise patterns in stereo image pairs, which can result in unrealistic and distracting visual artifacts, causing nausea and headaches due to spatial mismatch of noise intensities.
Innovation Solution
The implementation of an image processing system that removes embedded noises from stereo image pairs and applies desired noise patterns correlated with depth information, adjusting spatial resolutions based on object depth to ensure noise patterns align with 3D objects or image details, thereby enhancing perceptual accuracy and realism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise reduction techniques are applied to RE and LE images, then undesirable noise is removed, but desirable noise (film grain simulation) is also removed, making images too clean to be perceived as realistic
Solution Approach 1:
The patent applies different noise characteristics to different depth regions in the 3D image. By segmenting the image into multiple depth layers and applying appropriate noise patterns to each layer, the system preserves realistic film grain simulation while removing undesirable digital noise. This local differentiation allows selective noise management based on depth position.
Solution Approach 2:
The patent modifies noise parameters (intensity, spatial frequency, temporal frequency) based on depth information. By dynamically adjusting noise characteristics according to the depth of different image regions, the system maintains realism in certain areas while reducing noise in others, resolving the contradiction between noise removal and realism preservation.
2Reliability
If distinct noise characteristics are present in left and right cameras, then each camera captures its own noise pattern, but noise mismatch causes spatial disparity in noise intensities leading to visual artifacts
Solution Approach 1:
The patent introduces depth information as an intermediary to mediate between the noise characteristics of left and right cameras. By using depth maps or disparity information, the system correlates noise patterns across stereo images, ensuring that noise appears at consistent spatial positions in both views, thereby eliminating visual artifacts while preserving individual camera capture quality.
Solution Approach 2:
The patent segments the stereo image pair into multiple depth layers and processes noise characteristics for each segment separately. This allows independent noise adjustment for left and right images at different depth positions, resolving the mismatch issue by treating each depth region as an independent processing unit with its own noise correlation requirements.
3Ease of operation
If uniform noise patterns are applied to all depth regions, then application is simple, but noise does not align with 3D objects causing perceptual inaccuracy
Solution Approach 1:
The patent dynamically adjusts noise pattern parameters based on depth information from the 3D scene. Instead of applying static uniform noise, the system varies noise characteristics (intensity, spatial frequency) according to the depth of different regions, making noise alignment adaptive to the 3D structure while maintaining reasonable operational simplicity through automated depth-based control.
Data Source
AI summary
Perceptually correct noises simulating a variety of noise patterns or textures may be applied to stereo image pairs each of which comprises a left eye (LE) image and a right eye (RE) image that represent a 3D image. LE and RE images may or may not be noise removed. Depth information of pixels in the LE and RE images may be computed from, or received with, the LE and RE images. Desired noise patterns are modulated onto the 3D image or scene so that the desired noise patterns are perceived to be part of 3D objects or image details, taking into account where the 3D objects or image details are on a z-axis perpendicular to an image rendering screen on which the LE and RE images are rendered.