Motion Adaptive Interpolation for High-Frequency Image Objects
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional motion adaptive mechanisms fail to effectively interpolate pixels for high-frequency motion image objects, such as vertically moving captions, leading to poor image quality due to inaccurate motion compensation and non-smooth edges.
Innovation Solution
An interpolation method and apparatus that estimates the motion speed of image objects across multiple image fields using a motion estimation module, determining pixel positions for accurate interpolation in a target image frame, and performs motion compensation to improve image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional motion adaptive mechanism is used for de-interlacing and motion compensation, then image frame quality is improved for static or low-motion objects, but high-frequency motion objects (such as vertically moving captions) cannot be interpolated effectively
Solution Approach 1:
The patent applies dynamics by adapting the motion compensation method based on the motion characteristics of different image regions. The system dynamically switches between conventional motion adaptive mechanism for static/low-motion objects and a new motion estimation method for high-frequency motion objects like vertically moving captions. This dynamic adaptation allows the system to optimize interpolation accuracy for different types of image content without compromising overall image frame quality.
Solution Approach 2:
The patent implements local quality by treating different regions of the image differently based on their motion characteristics. Instead of applying a uniform motion compensation method to the entire image, the system identifies regions with high-frequency motion (such as vertically moving captions) and applies specialized motion estimation and interpolation techniques only to those regions, while using conventional methods for the rest of the image. This localized approach improves interpolation accuracy for high-frequency motion objects without affecting the quality of static or low-motion areas.
2Device complexity
If conventional motion adaptive mechanism is used directly, then processing simplicity is maintained, but clear image frame cannot be generated for vertically moving captions with non-smooth edges
Solution Approach 1:
The patent applies segmentation by dividing the image processing task into separate handling for different types of image content. The system segments the image into regions with high-frequency motion characteristics (such as vertically moving captions with non-smooth edges) and regions without such characteristics. By segmenting the processing workflow, the system can apply complex motion estimation and interpolation techniques only to the necessary regions, maintaining overall processing simplicity while achieving clear image frames for high-frequency motion objects.
3Adaptability or versatility
If Moving Picture Experts Group standard or Discrete Cosine Transform information is used for motion compensation, then standard compatibility is achieved, but accurate motion compensation cannot be performed for image data not decoded by these standards
Solution Approach 1:
The patent applies universality by creating a motion compensation system that can handle multiple types of image data formats universally. The system is designed to work with both standard decoded image data (from Moving Picture Experts Group or Discrete Cosine Transform) and non-standard decoded image data. By implementing a universal motion estimation mechanism that can process various image formats, the system achieves both standard compatibility and accurate motion compensation for diverse image sources, including high-frequency motion objects that may not conform to standard decoding protocols.
Data Source
AI summary
An interpolation method, applied to image pictures, for interpolating at least one pixel into a position to be interpolated in a target image frame is disclosed. The interpolation method includes receiving a plurality of image fields having a corresponding image object, estimating a motion speed of the image object according to a distance between a first pixel position to which the image object located in a first image field of the plurality of image fields and a second pixel position to which the image object located in a second image field of the plurality of image fields, determining the pixel from the plurality of image fields according to the motion speed of the image object, and interpolating the pixel into the position to be interpolated in the target image frame.