2x2 Block Image Compression for Exact LCD Bit Rate Control
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Solution Overview
Problem
Conventional image compression techniques for LCD DCC devices suffer from subjective picture quality deterioration, increased decoder complexity, and inability to achieve exact bit rate control, particularly affecting the performance of TFT-LCD panels.
Innovation Solution
A data compression method using Differential Pulse Code Modulation (DPCM) and Pulse Code Modulation (PCM) techniques that selectively compress image data in units of 2x2 blocks, allowing for exact bit rate control and minimizing picture quality deterioration when images shift, by calculating differences and truncating data accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If transform coding compression (JPEG, H.264) is applied to compress image data to 1/2-1/3 the size, then the data storage requirement is reduced, but subjective picture quality deteriorates due to edge crushing artifacts
Solution Approach 1:
The patent divides the image into 2x2 pixel blocks as the basic processing unit. This fine-grained segmentation allows the system to process and compress small groups of pixels together, preserving local spatial relationships and edge information while achieving compression. By operating on 2x2 blocks rather than individual pixels or larger macroblocks, the method maintains better picture quality at compressed bit rates.
Solution Approach 2:
The patent employs variable bit allocation for different color components (R, G, B) within each 2x2 block based on their importance and variance. By dynamically adjusting the number of bits allocated to each component's difference data, the system optimizes picture quality while achieving the target compression ratio. This parameter change strategy allows selective preservation of visually important information.
2Quantity of substance
If transform coding compression is applied, then the data storage requirement is reduced, but the decoder complexity significantly increases due to critical path requirements
Solution Approach 1:
The patent extracts and removes the complex transform coding and entropy decoding stages from the compression system. Instead, it uses simple differential encoding where only the difference between current and reference pixel values is stored, along with minimal mode information. This extraction of complex operations dramatically reduces decoder complexity while maintaining compression efficiency.
Solution Approach 2:
The patent replaces complex, expensive decoding algorithms with simple, inexpensive operations. The decoder only needs to perform basic arithmetic (adding stored difference values to reference values) rather than complex inverse transforms and entropy decoding. This substitution with cheaper operations reduces hardware complexity and power consumption.
3Quantity of substance
If H.264 standard with intra prediction is used, then the compression ratio is improved, but the amount of memory use and decoder complexity further increase
Solution Approach 1:
The patent uses 2x2 pixel block segmentation as the basic unit for compression, which is finer than the typical 16x16 or 8x8 macroblocks used in H.264. This fine segmentation reduces the amount of prediction data and mode information that needs to be stored and processed, thereby reducing memory usage and decoder complexity while maintaining compression efficiency.
Solution Approach 2:
The patent removes the intra prediction mechanism entirely from the system. Instead of performing complex prediction operations and storing prediction mode information, the method simply stores the difference between actual pixel values and reference values. This extraction of the prediction mechanism eliminates the associated memory and computational requirements.
4Quantity of substance
If image data is compressed using conventional methods, then the data storage requirement is reduced, but the ability to achieve exact bit rate control is lost
Solution Approach 1:
The patent employs dynamic bit allocation strategies where the number of bits allocated to each 2x2 block and each color component is adjusted based on the actual image content characteristics. By dynamically adapting the compression parameters to match the local image properties, the system can precisely control the total bit rate while maintaining optimal picture quality. This dynamic approach enables exact bit rate control that static compression methods cannot achieve.
Data Source
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AI summary
A method, medium, and system compressing and/or reconstructing image data. The data compression method includes compressing current data according to a plurality of modes for compressing current data, determining whether the current data compressed according to the plurality of modes can be represented by a fixed length of bits, selecting a mode from among modes in which the compressed current data can be represented by the fixed length of bits, and outputting the compressed current data according to the selected mode. Accordingly, it is possible to significantly lower the complexity of an image encoder/decoder system, and exactly meet a picture-based Control Bit Rate (CBR) suitable for a Liquid Crystal Display Dynamic Capacitance Compensation (LCD DCC) device/system.