Image Processing Device Coding Control for HDR Signal Adaptation
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Solution Overview
Problem
Existing devices involved in signal conversion for coding, decoding, and reproducing video images struggle to adapt to diversified video image signal expressions, leading to inadequate image quality, particularly in high dynamic range (HDR) and wide color gamut (WCG) scenarios.
Innovation Solution
An image processing system that controls the code amount assigned to each partial region based on the transfer function, optimizing quantization steps to maintain image quality by scaling the quantization step according to the intensity of luminance or chrominance components, and adjusting the prediction residual and mode code amounts in the cost evaluation formula to suit HDR and SDR video images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing devices use standard dynamic range (SDR) coding schemes, then coding efficiency is maintained, but image quality deteriorates in high dynamic range (HDR) scenarios with loss of grayscale information
Solution Approach 1:
The patent implements dynamic adaptation by detecting whether the input signal is HDR or SDR and automatically adjusting the coding parameters accordingly. The quantization step and cost evaluation formula are dynamically modified based on the signal type, enabling the device to maintain optimal performance across different dynamic range requirements without requiring separate dedicated systems.
Solution Approach 2:
The patent changes key coding parameters including the quantization step and cost evaluation formula based on the input signal characteristics. For HDR signals, the quantization step is adjusted to preserve grayscale information, and the cost evaluation formula is modified to account for the different luminance characteristics, thereby resolving the contradiction between maintaining standard coding efficiency and adapting to HDR requirements.
2Productivity
If quantization step is increased to improve coding efficiency, then compression ratio improves, but image quality deteriorates due to loss of grayscale information
Solution Approach 1:
The patent applies different quantization strategies to different parts of the image based on luminance intensity. In highlight regions where grayscale preservation is critical for HDR, a smaller quantization step is used to maintain detail, while in other regions a larger quantization step can be applied to improve compression. This local differentiation resolves the contradiction between overall coding efficiency and preservation of critical grayscale information.
3Device complexity
If standard cost evaluation formula is used for mode selection, then coding complexity is reduced, but coding efficiency deteriorates for HDR signals
Solution Approach 1:
The patent modifies the cost evaluation formula parameters specifically for HDR signals, adjusting the weightings and thresholds to account for the different characteristics of high dynamic range content. This allows the mode selection process to be optimized for HDR while maintaining a similar overall structure to the standard formula, thereby improving coding efficiency without excessively increasing complexity.
Data Source
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AI summary
[Object] To provide satisfactory image quality irrespective of signal expression schemes. [Solution] Provided is an image processing device including: a coding unit that codes an image acquired on the basis of a transfer function related to conversion between light and an image signal; and a control unit that controls coding processing executed by the coding unit, on the basis of the transfer function. The control unit may control a coding amount assigned to each partial region of the image in the coding unit, on the basis of the transfer function. The control unit may control a prediction residual coding amount or a mode coding amount for mode selection when the image is coded in the coding unit, on the basis of the transfer function.