Scanned Film Noise Reduction Through Repeated Pixel Sampling
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Solution Overview
Problem
Current methods for film scanning fail to effectively eliminate scanner noise below visual perception, particularly in High Dynamic Range (HOR) formats, leading to distracting artifacts in the finished digital video product.
Innovation Solution
A programmable scanner is configured to obtain multiple scans of a film frame, calculate a noise statistic (such as median or average) across these scans, and assign true pixel values to generate scanner noise-reduced digital image data, storing it if the noise is below a visibility threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If multiple scans are obtained and noise statistics are calculated to reduce scanner noise, then scanner noise visibility is reduced, but scanning time and processing complexity increase
Solution Approach 1:
The patent applies partial action by obtaining a limited number of scans (typically 3-5) rather than exhaustive scanning, and using statistical methods (median, mean, or mode) to estimate true pixel values. This partial approach achieves sufficient noise reduction for most practical applications without the excessive time cost of scanning the same frame numerous times or using more complex denoising algorithms.
Solution Approach 2:
The patent changes the parameter of scan repetition count to optimize the balance between noise reduction and time consumption. By adjusting how many times a frame is scanned and processed, the system can adapt to different noise levels and time constraints, achieving acceptable noise reduction with minimal time investment.
2Object-affected harmful factors
If multiple scans are obtained and noise statistics are calculated to reduce scanner noise, then scanner noise visibility is reduced, but processing complexity increases
Solution Approach 1:
The patent uses simple statistical operations (calculating median, mean, or mode of pixel values across multiple scans) rather than complex denoising algorithms. This partial approach provides sufficient noise reduction without requiring sophisticated processing complexity, maintaining computational efficiency.
Solution Approach 2:
The patent creates multiple copies of the same frame through repeated scanning and uses straightforward statistical comparison to determine the true value. This copying approach with simple statistical analysis is less complex than attempting to model and remove noise through advanced image processing techniques.
3Manufacturing precision
If scanner noise is reduced through multiple scans and statistical processing, then image quality improves, but productivity decreases
Solution Approach 1:
The patent applies partial action by processing only a limited number of scans (typically 3-5) rather than continuously scanning, and using quick statistical methods to determine true pixel values. This achieves acceptable image quality improvement without excessively slowing down the overall film conversion productivity.
Solution Approach 2:
The patent adjusts the parameter of scan repetition count to optimize the balance between image quality and conversion speed. By changing how many times frames are scanned and processed, the system can adapt to different quality requirements while maintaining reasonable productivity levels.
Data Source
AI summary
A method for preparing digital image data from an analog image input by scanning, and reducing visibility of the scanning noise, may include estimating a visibility of scanning noise, and a number of scanning samples needed to reduce scanning noise to below a visible threshold. Related methods include scanning, by an analog-to-digital image scanner, an analog image for multiple iterations, resulting in digital image data for each of the iterations; calculating a noise statistic for individual pixels of digital image data across the iterations; determining true values of individual pixels of the digital image data based on the noise statistic for each of the individual pixels and generating scanner noise reduced digital image data wherein pixels are assigned their respective ones of the true values; and saving the scanner noise reduced digital image data in a computer memory.