Noise Estimation for Mixed HDR Image Signals
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Solution Overview
Problem
Conventional methods for estimating noise in high dynamic range (HDR) images synthesized from image signals with different exposure times are inaccurate due to varying noise characteristics with exposure time, limiting image quality improvement.
Innovation Solution
An image processing apparatus and method that estimates noise in mixed image signals based on a mix ratio, noise characteristic coefficients, and exposure time ratios, allowing for noise removal processing using selected image signals and differences between image signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional noise estimation methods are used for HDR images synthesized from image signals with different exposure times, then the noise estimation process is simple, but the noise cannot be accurately estimated because the noise characteristic varies depending on the exposure time
Solution Approach 1:
The patent applies parameter changes by introducing exposure time as a variable parameter in the noise estimation formula. The noise estimation equation is modified to include the exposure time ratio (Te2/Te1) multiplied by the noise characteristic coefficient, allowing the estimation to adapt to different exposure conditions. This transforms the fixed-parameter conventional method into a dynamic parameter-based method that accurately reflects the exposure-dependent noise characteristics.
Solution Approach 2:
The patent implements dynamics by making the noise estimation process adaptive to varying exposure times. Rather than using a static noise estimation approach, the system dynamically adjusts the noise characteristic based on the ratio of exposure times between the first and second image signals. This dynamic adjustment allows the noise estimation to evolve with changing exposure conditions, resolving the contradiction between accuracy and complexity.
2Adaptability or versatility
If image signals with different exposure times are mixed to create HDR images, then the dynamic range is improved, but the noise characteristic becomes complex and varies with exposure time
Solution Approach 1:
The patent uses parameter changes to maintain noise characteristic consistency despite varying exposure times. By incorporating the exposure time ratio (Te2/Te1) as a scaling parameter in the noise estimation formula, the system adjusts the noise characteristics to remain consistent across different exposure conditions. This parameter adjustment ensures that the mixed HDR image maintains reliable and consistent noise properties throughout the dynamic range.
3Manufacturing precision
If noise removal processing is performed without accurate noise estimation, then the processing speed is fast, but sufficient improvement in image quality cannot be achieved
Solution Approach 1:
The patent applies preliminary action by performing accurate noise estimation before noise removal processing. The noise characteristic is estimated in advance using the exposure time ratio and noise characteristic coefficient, creating a reliable noise profile that guides subsequent noise removal operations. This preliminary estimation step ensures that the noise removal process is both efficient and effective, achieving high image quality improvement without excessive processing time.
Data Source
AI summary
A noise of an image signal generated by mixing a plurality of image signals is accurately estimated. In an image processing apparatus including an input unit and an estimation unit, a mixed image signal is input to the input unit, the mixed image signal being obtained by mixing a plurality of image signals with different exposure times that have been generated by an image sensor, on a basis of a predetermined mix ratio. The estimation unit is configured to estimate a mixed image signal noise being a noise of the mixed image signal, on a basis of the mix ratio, a noise characteristic coefficient indicating a noise characteristic of the image sensor, and a ratio between the exposure times in the plurality of image signals.