Pixel-Level Power Estimation for Image Processing Circuits
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Solution Overview
Problem
Current power consumption estimation methods for electronic system level (ESL) are inadequate as they do not account for image content, leading to rough estimates and inability to accurately reflect actual power consumption in image processing circuits.
Innovation Solution
A power consumption estimation method and apparatus that estimate power consumption by performing a pixel-by-pixel estimation procedure, obtaining pixel energy consumption values based on pixel content information, and accumulating these values to determine row power consumption, using a processor and memory to execute instructions and a conversion circuit to provide retrieval signals for energy consumption estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If power consumption estimation is performed only based on hardware configuration, then the estimation process is simple, but the measurement precision is insufficient and cannot reflect actual power consumption
Solution Approach 1:
The patent segments the image processing task into individual pixel operations and further divides power consumption estimation into hardware configuration parameters and image content parameters. By processing each pixel independently and accumulating results, the system achieves comprehensive power estimation without requiring complex full-system simulation, thus improving measurement precision while controlling complexity.
Solution Approach 2:
The patent performs preliminary extraction of image content features (such as pixel intensity, color information, and spatial relationships) before the actual power consumption calculation. This preliminary action allows the estimation model to directly use preprocessed features, avoiding complex real-time analysis during power estimation and reducing overall computational complexity while maintaining high precision.
2Measurement precision
If existing power consumption models are used that do not involve input signal content, then the device complexity is low, but the measurement precision of power consumption estimation deteriorates
Solution Approach 1:
The patent applies local quality by creating different power consumption calculation models for different types of pixels based on their content characteristics. Instead of using a single uniform model, the system adjusts calculation parameters according to local image features (such as edge regions vs. smooth regions), which significantly improves estimation accuracy without requiring a complete complex model for the entire image.
Solution Approach 2:
The patent dynamically changes estimation parameters based on image content characteristics. By detecting image features such as brightness, contrast, and spatial frequency, the system adjusts power consumption parameters accordingly, allowing the same hardware model to accurately estimate power for different image types without increasing structural complexity.
Data Source
AI summary
A power consumption estimation method is applied to an image with N rows of pixels, and comprises a pixel estimation procedure comprising performing an estimation sub-procedure pixel by pixel for each of a plurality of pixels in one row of the N rows of pixels to obtain a plurality of pixel energy consumption values respectively corresponding to the plurality of pixels in said one row of the N rows, and obtaining a row power consumption value corresponding to said one row of the N rows according to the plurality of pixel energy consumption values. The estimation sub-procedure comprises obtaining pixel content information corresponding to one of the plurality of pixels, and determining the pixel energy consumption value according to the pixel content information. The pixel energy consumption value indicates pixel energy consumption generated by performing a predetermined image processing procedure for said one of the plurality of pixels.