Camera Defogging via Histogram Segmentation and Intensity Stretching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Legacy cameras with limited processing power struggle to perform real-time defogging of images and videos, especially when streaming, and monitoring stations lack access to raw image data due to compression, making it difficult to discern objects obscured by fog.
Innovation Solution
Implementing a method within cameras to determine a histogram of intensity values, identify a breakpoint, and generate output intensity values by compressing low-mode and stretching high-mode pixels, enabling defogging and improving contrast without requiring significant processing power or raw data access at the monitoring station.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time defogging processing is performed in legacy cameras, then object visibility is improved, but processing power requirements increase
Solution Approach 1:
The patent segments the histogram into two distinct modes (first mode and second mode) separated by a breakpoint. This segmentation allows independent processing of fog-affected pixels (second mode) and non-fog pixels (first mode), enabling targeted defogging operations that reduce overall processing requirements while maintaining effectiveness.
Solution Approach 2:
The patent transforms pixel intensity values by compressing the first mode and stretching the second mode relative to the breakpoint. This parameter transformation enhances the visibility of objects in foggy regions while adapting to the specific characteristics of each image, achieving improved visibility without requiring excessive processing power.
2Loss of energy
If video streams are compressed for transmission, then bandwidth usage is reduced, but access to raw image data for defogging is lost
Solution Approach 1:
The patent performs defogging processing at the camera端 before video compression and transmission. By completing the image enhancement operation in advance, the system eliminates the need to transmit raw image data to monitoring stations, thereby reducing bandwidth requirements while still providing defogged video streams.
Solution Approach 2:
The camera device autonomously performs defogging processing on its own captured images without requiring external processing resources. This self-service approach allows the camera to independently enhance image quality, freeing up bandwidth and eliminating the need for monitoring stations to access raw data for defogging operations.
3Measurement precision
If histogram processing is applied to all pixels, then defogging effectiveness is improved, but processing time increases
Solution Approach 1:
The patent applies different processing characteristics to different pixel groups based on their intensity values. Pixels in the second mode (above breakpoint) representing fog-affected regions receive stretching treatment, while pixels in the first mode (below breakpoint) receive compression treatment. This localized processing approach optimizes defogging effectiveness for relevant pixels while reducing unnecessary processing of other pixels.
Data Source
AI summary
A method and system are disclosed. The method may include determining a histogram of intensity values for pixels in image sensor data in which the histogram is bimodal. The method may include determining a breakpoint between the two modes. The histogram may include a first distribution of intensity values below the breakpoint and a second distribution of intensity values above the breakpoint. The method may include generating output intensity values. Generating output intensity values may include compressing the first distribution of intensity values of the pixels with intensity values below the breakpoint, stretching the second distribution of intensity values of the pixels with intensity values above the breakpoint, and generating an output image based on the output intensity values.