Frequency Domain Image Enhancement Reducing Computational Complexity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current image enhancement methods for surveillance and other applications are computationally expensive, making them inefficient for real-time processing and requiring significant resources.
Innovation Solution
Implementing frequency domain techniques for upsampling and filtering instead of pixel domain methods, which allows for sharper edge detection and reduced computational complexity, enabling faster and more accurate image enhancement and registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel domain techniques are used for image enhancement, then image quality can be improved, but computational cost and processing time increase significantly
Solution Approach 1:
The patent replaces pixel-domain processing methods with frequency-domain processing methods. Specifically, it uses Fast Fourier Transform (FFT) to convert images from spatial domain to frequency domain, performs enhancement operations in the frequency domain, and then converts back to spatial domain. This substitution reduces computational complexity from O(N^2) in pixel domain to O(N log N) in frequency domain, significantly improving processing speed while maintaining image quality.
Solution Approach 2:
The patent transforms the representation parameters of image data from spatial coordinates (pixel domain) to frequency coordinates (frequency domain). By changing the domain parameter, the same image enhancement task can be performed with different computational characteristics. The frequency domain representation allows for more efficient filtering and enhancement operations, reducing computational cost while preserving measurement precision.
2Manufacturing precision
If traditional image enhancement methods are applied, then image resolution can be enhanced, but memory usage and computational resources increase
Solution Approach 1:
The patent substitutes traditional pixel-domain enhancement algorithms with frequency-domain algorithms. By performing enhancement operations on the frequency spectrum rather than on individual pixels, the method reduces memory requirements. The frequency domain representation allows for compact storage of image characteristics, and operations can be performed on compressed representations, thereby reducing the quantity of data that must be stored and processed.
3Measurement precision
If computationally expensive enhancement methods are used, then detection accuracy of low-level features improves, but processing time and resource consumption increase
Solution Approach 1:
The patent replaces computationally intensive pixel-domain processing with efficient frequency-domain processing using FFT algorithms. This substitution maintains the ability to detect low-level features accurately while dramatically reducing processing time. The frequency domain transformation enables parallel processing of frequency components, and the inverse transform efficiently reconstructs the enhanced image, minimizing time loss while preserving detection accuracy.
Data Source
AI summary
Embodiments of a method and apparatus for image enhancement are generally described herein. In some embodiments, the method includes accessing two or more sets of first pixel data representative of two or more images of a physical object. The method can further include transforming the two or more sets of pixel data to generate two or more sets of frequency domain data. The method can further include upsampling each of the two or more sets of frequency domain data to generate a set of upsampled frequency domain data. The method can further include re-transforming the set of upsampled frequency domain data to generate two or more sets of second pixel data. The method can further include combining two or more sets of second pixel data to generate an enhanced image of the physical object. Other example methods, systems, and apparatuses are described.