Multi-Viewpoint Image Coding Quality Evaluation
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Solution Overview
Problem
Conventional evaluation methods for coding distortion in linear blending displays fail to distinguish between different distortion cases, leading to suboptimal subjective image quality due to identical evaluation values for distinct distortion scenarios, which affects the selection of appropriate coding modes for intermediate viewpoint images.
Innovation Solution
An evaluation device and method that assesses coding quality by associating pixel values of original and decoded images across multiple viewpoints, using a modified formula (SELBD) to differentiate between distortion cases and select optimal coding modes based on viewer perspective and movement patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If independent evaluation of coding distortion is performed for each viewpoint using conventional square error, then evaluation process is simple, but distortion amounts in intermediate viewpoint images cannot be correctly taken into consideration
Solution Approach 1:
The patent merges the evaluation of coding distortion across multiple viewpoints by calculating distortion for both the first viewpoint image and the second viewpoint image, then using these combined results to evaluate the intermediate viewpoint image. This is achieved through the evaluation unit that simultaneously considers pixel values from multiple viewpoints to assess the overall coding quality, rather than evaluating each viewpoint independently.
Solution Approach 2:
The patent introduces an intermediary evaluation approach where the coding distortion of the intermediate viewpoint image is evaluated not directly from its own pixel values alone, but through the pixel values of the first and second viewpoint images that serve as intermediaries. The evaluation unit uses these intermediary viewpoint images to infer and evaluate the distortion in the intermediate viewpoint, enabling accurate assessment without directly processing the intermediate image data.
2Productivity
If conventional square error is used for coding distortion evaluation, then calculation is simple, but different distortion cases yield identical evaluation values leading to suboptimal coding mode selection
Solution Approach 1:
The patent applies local quality evaluation by considering the specific characteristics of distortion at different viewpoints. Instead of using a uniform square error calculation that treats all pixel differences equally, the evaluation unit assesses coding distortion locally at each viewpoint (first and second viewpoints) and then combines these local evaluations to determine the overall coding quality for the intermediate viewpoint, enabling more nuanced coding mode selection.
Solution Approach 2:
The patent changes the evaluation parameter from a simple square error calculation to a multi-viewpoint-based distortion evaluation. By incorporating pixel values from multiple viewpoints and calculating distortion relative to these reference viewpoints, the evaluation method transforms the single-parameter square error into a multi-dimensional assessment that can distinguish between different distortion cases and guide better coding mode selection.
Data Source
AI summary
An evaluation device for evaluating coding quality of coded data of an image for a first viewpoint in a multi-viewpoint image, the evaluation device includes an evaluation unit that evaluates coding quality of coded data relating to the first viewpoint by associating a pixel value of an original image for the first viewpoint, a pixel value obtained from the coded data relating to the first viewpoint, a pixel value of an original image for a second viewpoint that is different from the first viewpoint and a pixel value obtained from coded data relating to the second viewpoint with one another.