LCD Interpolation Device Using Segmented Bit Processing
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Solution Overview
Problem
Existing liquid crystal display systems face challenges in accurately interpolating image signals, particularly for moderate gray scale differences between frames, leading to potential image resolution issues due to imprecise interpolation equations.
Innovation Solution
An improved interpolation device comprising a signal delay memory, look-up table, and arithmetic logic unit (ALU) that uses a second-order interpolation equation to precisely account for differences in both significant and less significant bits of image signals, reducing interpolation errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If an imprecise linear and symmetrical interpolation equation is used to handle small differences of gray scale, then the storage memory space needed by the LUT is limited, but the drive voltage accuracy deteriorates for moderate differences of gray scales between frames
Solution Approach 1:
The patent divides the interpolation process into two segments: (1) LUT-based correction for significant bits (MSBs) handling large gray scale differences, and (2) polynomial interpolation for less significant bits (LSBs) handling small gray scale differences. This segmentation allows each method to operate in its optimal range, resolving the contradiction between storage efficiency and accuracy.
Solution Approach 2:
The patent applies different interpolation methods to different bit positions (local quality): significant bits use LUT-based correction while less significant bits use polynomial interpolation. This localized approach ensures high accuracy for moderate gray scale differences while maintaining reasonable storage requirements.
2Quantity of substance
If only the more significant bits (MSB's) of the pixel data are used in the LUT, then the storage memory space is limited, but the interpolation accuracy for moderate gray scale differences deteriorates
Solution Approach 1:
The patent segments pixel data into significant bits (MSBs) and less significant bits (LSBs), applying different processing methods to each segment. MSBs are handled by LUT for coarse correction, while LSBs are handled by polynomial interpolation for fine adjustment, achieving both storage efficiency and high accuracy.
Solution Approach 2:
The patent introduces polynomial interpolation as an intermediary mechanism that bridges the gap between LUT-based coarse correction and the need for fine-grained accuracy. This intermediary process uses the LSBs to refine the drive voltage calculation without requiring extensive LUT storage.
3Device complexity
If a linear and symmetrical interpolation equation is used, then the system complexity is reduced, but the ability to display subtle changes of gray scale deteriorates
Solution Approach 1:
The patent applies different interpolation characteristics to different bit positions: significant bits use symmetrical LUT-based correction while less significant bits use asymmetric polynomial interpolation. This local differentiation enables precise representation of subtle gray scale changes without requiring a completely complex system.
Solution Approach 2:
The patent creates a composite interpolation system combining LUT-based correction and polynomial interpolation. This composite approach leverages the simplicity of LUT for coarse corrections and the precision of polynomial math for fine adjustments, achieving high gray scale precision without excessive overall complexity.
Data Source
AI summary
In an interpolation device that is used for driving a liquid crystal display (LCD), a memory stores an image signal representing a previously displayed image frame. A look-up table (LUT) stores plural reference data corresponding to differences between values of high order bits of a present image signal and a previous image signal. An arithmetic unit receives low order bits of the present image signal, low order bits of the previous image signal, and the reference data from the LUT to output a corrected image signal. The arithmetic unit applies a first second-order interpolation equation when the high order bits of the present image signal are identical to the high order bits of the previous image signal and applies a second second-order interpolation equation, which is different from the first second-order interpolation equation, when the high order bits of the present image signal are different from the high order bits of the previous image signal.