Dynamic Video Quality Analysis Using Texture and Color Attributes
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Solution Overview
Problem
Current digital video quality analysis methods fail to effectively unify complex factors such as shapes, textures, and color attributes, making it difficult to assess and modify digital video content objectively, especially when a reference video is involved.
Innovation Solution
An apparatus and method that analyze texture attributes when a reference video exists and color attributes when it does not, displaying results on a single screen with numerical values and graphs, using a video analyzing unit and result displaying unit to determine main and minor component analysis factors based on importance weights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If general video quality assessment methods are used, then video quality can be assessed, but the assessment does not accurately reflect human subjective evaluation when reference videos are involved
Solution Approach 1:
The patent implements dynamic adaptation of analysis factors based on the presence or absence of reference videos. When reference videos are available, the system dynamically switches to using texture attributes as main analysis factors; when reference videos are unavailable, it switches to using color attributes as main analysis factors. This dynamic adjustment resolves the contradiction by making the assessment system adaptable to different reference video conditions while maintaining accurate measurement of video quality according to human subjective evaluation criteria.
2Measurement precision
If multiple video quality factors are analyzed, then comprehensive video quality assessment is achieved, but the complexity of unifying these factors increases
Solution Approach 1:
The patent segments video quality assessment into distinct analysis factors: texture attributes (when reference videos exist) and color attributes (when reference videos do not exist). By dividing the complex task of unified factor assessment into separate, condition-based segments, the system achieves comprehensive video quality assessment while reducing the complexity of unifying all factors simultaneously. Each segment can be processed independently according to its specific characteristics.
Solution Approach 2:
The patent applies different analysis factors (texture vs. color) to different local conditions (presence or absence of reference videos). Instead of applying a single unified set of factors to all video quality assessment scenarios, the system uses local quality assessment by selecting appropriate factors based on the specific context, thereby achieving comprehensive assessment while managing complexity through localized factor selection.
3Measurement precision
If subjective assessment criteria are used, then human perception accuracy is captured, but the subjectivity makes standardization difficult
Solution Approach 1:
The patent changes the parameters used for video quality assessment based on the assessment context. By switching between texture attributes and color attributes as main analysis factors depending on the presence of reference videos, the system captures different aspects of human perception in different contexts while maintaining standardized processing procedures. This parameter change approach allows the system to reflect human subjective accuracy without requiring complete standardization of all assessment criteria.
Data Source
AI summary
An apparatus and method for automatically analyzing digital video quality are provided. The apparatus for automatically analyzing digital video quality includes a video analyzing unit and a result displaying unit. The video analyzing unit analyzes a texture attribute of an input video and analyzes a color attribute of the input video, thereby obtaining a texture attribute analysis result and a color attribute analysis result. The result displaying unit determines whether a reference video for video quality analysis exists or not. When the reference video exists, the result displaying unit determines the texture attribute analysis result as a main component analysis result and the color attribute analysis result as a minor component analysis result, respectively, and displays the determined analysis results on a screen in a form of numerical values and graphs together with the input video. On the contrary, when the reference video does not exist, the result displaying unit determines the texture attribute analysis result as the minor component analysis result and the color attribute analysis result as the major component analysis result, respectively, and displays the determined analysis results on the screen in a form of numerical values and graphs together with the input video. Accordingly, the digital video quality can be automatically analyzed and displayed.