Depth Map Generation Using Gradient Regions and Color Models
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Solution Overview
Problem
The conversion of 2D images to stereoscopic images is hindered by the computationally intensive depth map generation process, which often introduces artifacts, particularly in complex images with high detail, where accurately identifying high-focus regions is challenging.
Innovation Solution
The method involves retrieving a 2D image, identifying high gradient regions, forming expanded regions around them, and deriving a color model from out-of-focus areas to generate a depth map for stereoscopic conversion, utilizing the color model to assign depth values to pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional depth map generation methods are used to convert 2D images to stereoscopic images, then depth information can be obtained, but the process is computationally intensive and introduces artifacts particularly in complex images with high detail
Solution Approach 1:
The patent segments the image processing task by separating high gradient regions (containing edges and detailed structures) from out-of-focus regions. By identifying and protecting high gradient regions through expanded region formation, the method processes different image areas with appropriate strategies, reducing overall computational complexity while maintaining depth map accuracy in critical areas.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image. High gradient regions receive special treatment through expanded region formation to preserve edges and details, while out-of-focus regions are used for color model derivation. This local differentiation reduces artifacts and improves depth map accuracy without requiring computationally intensive processing across the entire image.
2Measurement precision
If traditional depth map generation methods are used, then depth information can be extracted, but artifacts are introduced particularly in regions with high detail and complex structures
Solution Approach 1:
The patent applies preliminary anti-action by forming expanded regions around high gradient areas before depth map generation. This pre-processing step proactively protects edge and detail regions from artifact introduction during subsequent processing. By establishing these protective expanded regions in advance, the method prevents the harmful effects of traditional methods that would otherwise introduce artifacts in high-detail areas.
Solution Approach 2:
The patent converts the challenge of high gradient regions (which traditionally cause artifacts) into a benefit by using them as the basis for forming expanded protective regions. Instead of treating high detail areas as problem zones to be avoided, the method leverages their gradient characteristics to identify and protect them, transforming what was previously a source of artifacts into a guide for improving accuracy.
3Measurement precision
If traditional methods process the entire image uniformly, then complete coverage is achieved, but computational intensity increases significantly
Solution Approach 1:
The patent applies partial action by focusing computational resources on identifying and processing high gradient regions and their expanded areas, rather than uniformly processing the entire image. By deriving the color model specifically from out-of-focus regions and using expanded regions to guide depth map generation in high-detail areas, the method achieves effective coverage where it matters most while reducing overall computational intensity.
Data Source
AI summary
Various embodiments are disclosed for generating depth maps. One embodiment is a method implemented in an image processing device. The method comprises retrieving, by the image processing device, a (2D) image; and determining, by the image processing device, at least one region within the (2D) image having a high gradient characteristic relative to other regions within the (2D) image. The method further comprises identifying, by the image processing device, an out-of-focus region based on the at least one region having a high gradient characteristic; and deriving, by the image processing device, a color model according to the out-of-focus region. Based on the color model, the image processing device provides a depth map for (2D)-to-stereoscopic conversion.