Image Signal Processor Gradation Detection and Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image signal processors face challenges in enhancing image quality and reducing power consumption while effectively processing pixel signals from various areas of an image sensor, such as flat, edge, and gradation areas.
Innovation Solution
An image signal processor is designed with a gradation detection module that estimates gradients and calculates variance values to generate a gradation map, which is used by a correction module to correct pixel signals, thereby improving image quality by distinguishing and processing different areas within an image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If pixel signals are processed uniformly across all areas, then processing simplicity is maintained, but image quality deteriorates due to inability to distinguish different area characteristics
Solution Approach 1:
The image processing is segmented by dividing the image into different area types (flat areas, edge areas, and gradation areas) based on gradient calculations. Each area type receives customized processing parameters, allowing the system to improve image quality for specific area characteristics without uniformly increasing complexity across the entire image.
Solution Approach 2:
Different processing parameters are applied to different local areas of the image based on their characteristics. Flat areas receive one type of processing, edge areas receive another, and gradation areas receive yet another. This local differentiation improves overall image quality while maintaining processing efficiency by not applying complex operations to all areas.
2Manufacturing precision
If comprehensive image processing is applied to all pixel signals, then image quality is improved, but power consumption increases
Solution Approach 1:
Instead of applying comprehensive image processing to all pixel signals, the system applies processing selectively based on area type. By identifying flat areas, edge areas, and gradation areas and applying appropriate processing only where needed, the system achieves good image quality while reducing overall power consumption compared to uniform comprehensive processing.
3Manufacturing precision
If gradient-based correction is applied to all pixel signals, then image quality is improved, but processing time increases
Solution Approach 1:
The processing time is reduced by segmenting the image into different area types and applying gradient-based correction only to specific area types that benefit from it. This selective approach maintains image quality improvement where needed while reducing overall processing time compared to applying gradient correction to all pixel signals uniformly.
Data Source
AI summary
An image signal processor includes a gradation detection module configured to receive a pixel signal from an external device and a correction module configured to receive the pixel signal. The correction module is connected to the gradation detection module. The gradation detection module is configured to estimate a gradient of the pixel signal, correct the pixel signal based on the gradient to generate a corrected pixel signal, calculate a first variance value based on the pixel signal, calculate a second variance value based on the corrected pixel signal, calculate a gradation probability value based on a comparison result between the first variance value and the second variance value, and generate a gradation map as information about the gradation probability value of the pixel signal. The correction module is configured to correct the pixel signal based on the gradation map.