Image blind restoration method based on COS function and Wiener filtering
By combining COS filtering and Wiener filtering, a multi-scale Gaussian space and an alternating iterative optimization strategy were constructed to solve the problem of ringing artifacts in remote sensing images and achieve high-quality image restoration.
CN120997087AActive Publication Date: 2025-11-21CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
2 Cites 0 Cited by
Patent Information
- Application Number
- CN202511519577.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-23
- Publication Date
- 2025-11-21
- Estimated Expiration
- 2045-10-23
AI Technical Summary
Technical Problem
Remote sensing images are often blurred and prone to ringing artifacts in edge areas due to environmental interference and noise during the imaging process. Existing Wiener filtering methods are not effective in the restoration process.
Method used
By combining COS filtering and Wiener filtering, and constructing a multi-scale Gaussian space and using an alternating iterative optimization strategy, the Laplacian operator is used to suppress blur kernel noise, and the frequency domain COS filter is combined to suppress ringing effects, thereby improving image clarity.
Benefits of technology
It effectively suppressed ringing artifacts in the image edge areas, improved the overall image restoration quality and visual effect, and maintained high definition.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention relates to the technical field of image processing, and particularly provides an image blind restoration method based on a COS function and Wiener filtering, comprising: acquiring a blurred image to be processed, constructing a blind deblurring model under a variational framework, an objective function of the blind deblurring model being used for synchronously estimating a low-rank clear image and a blurring kernel; solving the target function in the multi-scale Gaussian space through an alternating iteration optimization strategy, and estimating to obtain a low-rank clear image and a blurring kernel; and performing Wiener filtering on the blurred image by using the solved blurred kernel to obtain an initial restored image, and performing COS filtering on the initial restored image to obtain a final restored image. Wiener filtering and the COS filter are combined, smooth transition is carried out through the COS filter, and the ringing artifact problem existing in traditional Wiener filtering is effectively solved.
Need to check novelty before this filing date? Find Prior Art