Image Signal Processor Local White Balance Gain Correction
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Solution Overview
Problem
Existing image signal processors face challenges in accurately demosaicing images, particularly with locally bright objects, due to limitations in interpolation algorithms that can lead to noise and errors.
Innovation Solution
An image signal processor is designed with a local white balance gain calculator and corrector, along with a demosaicing corrector, to calculate and apply correction gains for red, green, and blue pixel data, reducing noise and errors by selectively applying smoothing-filtering to pixels with spot-shaped bright objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If interpolation algorithm is used to convert original image to complete RGB image, then image conversion is achieved, but noise and demosaicing errors occur in specific images
Solution Approach 1:
The patent applies local white balance gain correction by calculating separate correction gains for different local regions of the image. The LWBG calculator computes first and second correction gains for red and blue channels respectively, and the demosaicing corrector applies these gains locally to correct pixel data in specific regions, thereby improving demosaicing accuracy in locally bright objects without affecting the entire image uniformly.
Solution Approach 2:
The patent changes the white balance gain parameter dynamically based on local image characteristics. By calculating local white balance gains from pixel data in different regions and applying region-specific correction gains, the system adapts the white balance parameter to local conditions, resolving the contradiction between maintaining overall image conversion capability and improving local demosaicing accuracy.
2Reliability
If local white balance gain correction is applied to reduce demosaicing errors, then demosaicing accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the white balance correction process into distinct functional modules: an LWBG calculator for computing local white balance gains, an LWBG corrector for generating correction gains, and a demosaicing corrector for applying corrections to pixel data. This segmentation allows each module to perform a specific function efficiently, improving demosaicing accuracy while managing device complexity through modular design.
Solution Approach 2:
The patent performs preliminary calculation of local white balance gains before the main demosaicing correction process. The LWBG calculator computes correction gains in advance based on pixel data, and these pre-computed gains are then applied by the demosaicing corrector. This preliminary action separates the complex gain calculation from the correction application, improving overall system efficiency and managing complexity.
Data Source
AI summary
An image signal processor and an image signal processing method are disclosed. The image signal processor includes a local white balance gain (LWBG) calculator configured to calculate a first gain representing a ratio between red pixel data and green pixel data and a second gain representing a ratio between blue pixel data and green pixel data, a local white balance gain (LWBG) corrector configured to generate a first correction gain and a second correction gain by filtering each of the first gain and the second gain, and a demosaicing corrector configured to correct each of the red pixel data, the green pixel data, and the blue pixel data using the first correction gain and the second correction gain.