GPU-Based Pixel Correction for Camera Phone Image Quality
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Solution Overview
Problem
Camera phones face challenges in maintaining picture quality due to constraints on cost, weight, and size, and the degradation of detector components over time, leading to increased manufacturing costs and discard rates.
Innovation Solution
Incorporating a graphics processing unit (GPU) to post-process image data, identifying and compensating for defective pixel values by averaging neighboring pixel values, and applying correction factors stored in a lookup table to improve image quality without increasing device size or cost, and to extend the life of the device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If higher quality camera components are used to improve picture quality, then picture quality is improved, but device cost increases
Solution Approach 1:
The patent creates a digital copy of the detector array's performance characteristics by capturing test images and comparing them against reference images. This digital model allows the system to identify and compensate for defective pixels through software processing, eliminating the need for physically higher quality (and more expensive) detector components while maintaining acceptable picture quality.
Solution Approach 2:
The patent changes the approach from hardware-based quality improvement to software-based parameter adjustment. By characterizing each pixel's response and applying correction factors through image processing algorithms, the system adjusts parameters in the digital domain to compensate for hardware defects, achieving quality improvement without increased component cost.
2Reliability
If detector array quality checks are performed to ensure picture quality, then picture quality is maintained, but manufacturing cost increases due to discarded components
Solution Approach 1:
Instead of discarding detector arrays with minor defects, the patent creates a digital copy of their performance characteristics through test image capture. This allows defective pixels to be identified and compensated for through software correction, enabling the use of previously discarded components and reducing manufacturing waste.
Solution Approach 2:
The patent performs preliminary characterization of the detector array by capturing test images and comparing them against reference images during or after manufacturing. This preliminary action identifies defective pixels before the detector array is deployed, allowing for targeted compensation rather than complete discarding of faulty components.
3Productivity
If detector elements are used repeatedly to capture multiple images, then productivity is improved, but picture quality degrades due to component failure
Solution Approach 1:
The patent implements feedback by continuously monitoring detector element performance through test images and using this information to generate correction factors. These correction factors are applied to subsequent images captured by the same detector array, allowing the system to compensate for degradation and maintain picture quality over time despite repeated use.
Solution Approach 2:
The patent performs preliminary characterization of detector array performance by capturing test images and comparing them against reference images. This preliminary action establishes a baseline for what constitutes acceptable performance, enabling the system to detect and compensate for degradation as the detector array ages from repeated use.
Data Source
AI summary
Described is a device (e.g., a cell phone incorporating a digital camera) that incorporates a graphics processing unit (GPU) to process image data in order to increase the quality of a rendered image. The processing power provided by a GPU means that, for example, an unacceptable pixel value (e.g., a pixel value associated with a malfunctioning or dead detector element) can be identified and replaced with a new value that is determined by averaging other pixel values. Also, for example, the device can be calibrated against benchmark data to generate correction factors for each detector element. The correction factors can be applied to the image data on a per-pixel basis. If the device is also adapted to record and/or play digital audio files, the audio performance of the device can be calibrated to determine correction factors for a range of audio frequencies.