3D Depth Map Correction via Block Brightness Analysis
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Solution Overview
Problem
Conventional three-dimensional image conversion methods often generate erroneous depth maps when subjects with dark and light colors are arranged in specific configurations, leading to inaccurate rendering of image characteristics and degradation in picture quality.
Innovation Solution
An apparatus and method that analyze frame image data to identify image patterns and calculate per-pixel brightness values, correcting the initial depth map by classifying pixels into blocks and areas, and applying gain values to accurately adjust depth values based on spatial positions and brightness patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a depth map is generated based on statistical brightness and color characteristics of the image, then the depth map can effectively reflect various characteristics of the image, but when an image has characteristics that a subject exhibiting dark color is arranged ahead of a subject exhibiting light color, the depth map cannot accurately render the original characteristics of the image
Solution Approach 1:
The image is divided into multiple blocks, and each block is processed separately to determine depth values. This segmentation allows the algorithm to handle local brightness variations more effectively, preventing the misinterpretation of dark subjects as background elements, thus resolving the contradiction between general effectiveness and reliability under specific image characteristics.
Solution Approach 2:
The patent applies different processing strategies to different regions of the image based on local characteristics. By analyzing brightness relationships within local blocks rather than applying global statistical rules, the system maintains depth map reliability for images with dark subjects in front of light subjects while preserving the ability to reflect general image characteristics.
2Productivity
If conventional three-dimensional image conversion apparatuses determine depth values based on statistical brightness values, then the processing is simple and fast, but erroneous depth information is generated when dark-color subjects are positioned in front of light-color subjects
Solution Approach 1:
The image processing is segmented into block-level operations rather than pixel-level or global operations. This allows the system to maintain computational efficiency similar to conventional methods while improving accuracy by considering local brightness relationships within each block, thus resolving the contradiction between processing speed and depth value accuracy.
Solution Approach 2:
The patent performs additional local brightness comparisons within blocks beyond simple global statistical analysis. This partial extension of the processing - adding only the necessary local comparison step - maintains fast processing while eliminating erroneous depth assignments for dark subjects, balancing productivity and measurement precision.
Data Source
AI summary
Disclosed are an apparatus and method for correcting a depth map for a three-dimensional image, which are capable of accurately correcting an initially-generated depth map in accordance with characteristics of an image, thereby achieving an enhancement in picture quality of a three-dimensional image. The disclosed apparatus includes an original depth map generating unit for generating an original depth map for frame image data externally supplied to the original depth map generating unit, and a depth map correcting unit for analyzing the externally-supplied frame image data, calculating an image pattern of the frame image data and per-pixel brightness values of the frame image data, based on results of the analysis, and correcting the original depth map output from the original depth map generating unit, based on the calculated image pattern and the calculated brightness values, thereby generating a corrected depth map.