Complexity-Adaptive Image Processing for Low-Bit-Rate Encoding
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Solution Overview
Problem
Existing image processing systems face inefficiencies when constrained by low target bit rates or complex application scenarios, leading to issues such as insufficient sharpness or clarity due to mismatched settings between image signal processors and encoders.
Innovation Solution
The system adjusts parameters of both the image signal processor and encoder based on the complexity of input image frames, using parameter setters to optimize configuration parameters for improved performance, particularly in low bit rate or complex scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the image signal processor uses fixed configuration parameters, then the device complexity is reduced, but the image processing performance deteriorates under varying complexity conditions
Solution Approach 1:
The patent implements dynamic configuration parameters that automatically adjust based on the complexity of input image frames. The image signal processor transitions from a static, fixed-parameter system to a dynamic one where parameters are modified in real-time according to scene complexity metrics, resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The system changes configuration parameters of the image signal processor based on detected image complexity. By monitoring complexity metrics and adjusting parameters such as processing intensity, filter strength, or compression levels, the system adapts to varying input conditions without requiring multiple dedicated hardware configurations.
2Productivity
If the encoder uses aggressive compression to achieve low bit rate, then the productivity is improved, but the manufacturing precision of image quality deteriorates
Solution Approach 1:
The patent applies different processing and encoding strategies to different regions or portions of image frames based on their complexity. High-complexity regions receive more processing resources and less aggressive compression, while low-complexity regions use standard processing. This local differentiation maintains overall image quality while achieving efficient compression.
Solution Approach 2:
The system applies processing and compression actions selectively rather than uniformly across all image data. By identifying and focusing computational resources on complex regions that require more attention, the system achieves effective compression without uniformly sacrificing quality across the entire image.
3Manufacturing precision
If the image signal processor increases processing intensity to improve image quality, then the manufacturing precision is improved, but the use of energy increases
Solution Approach 1:
The system dynamically adjusts processing intensity parameters based on image complexity metrics. When input frames are simple, the processor uses lower intensity settings consuming less energy. When complexity increases, the system automatically increases processing intensity to maintain quality, optimizing the energy-quality tradeoff in real-time.
Data Source
AI summary
An apparatus and a method for outputting image data, and an electronic device are provided. The apparatus includes a first parameter setter, an image signal processor, and an encoder, wherein the first parameter setter sets a first configuration parameter for the image signal processor based on a complexity associated with an input image frame, wherein the image signal processor performs an image signal processing on at least one image frame to generate processed image data based on the first configuration parameter, wherein the encoder performs encoding processing on the processed image data to generate encoded image data. The apparatus and the method for outputting image data, and the electronic device of the present disclosure adjust parameters of the image signal processor and the encoder according to the complexity associated with an input image frame, thereby effectively improving the overall performance of image processing, encoding and compression.