Blind denoising for LiDAR signal based on high dimensional eigenvalue analysis

Infrared images play a crucial role in military reconnaissance, security monitoring, fire detection, and other tasks. However, due to the physical limitations of detectors, an infrared image often suffers from significant stripe noise. The presence of stripe noise significantly degrades image quality and subsequent processing, making the removal of such noise indispensable. In this study, we propose, to our knowledge, a novel low-rank decomposition model to separate the stripe noise components in infrared images. In comparison with existing algorithms for removing infrared stripe noise, our method takes into account the distinctiveness between stripe noise and information components. For the stripe noise component, we describe a column gradient domain low-rank prior and standard deviation weighted group sparsity prior. For the image information component, we employ a structure-aware gradient sparsity prior to suppress stripes while preserving the structural features of images. During the iterative solution process, we utilize both an initial solution based on minimizing column differences and an iteration step-size strategy based on variable acceleration to accelerate convergence. To validate the effectiveness of our proposed method, we conduct experiments to compare it with other destriping algorithms, demonstrating the superiority of our method from the perspectives of both subjective evaluation and objective metrics.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Blind denoising for LiDAR signal based on high dimensional eigenvalue analysis

Cited by 2 publications

References 14 publications

The Algorithm for Blind Multi-User Detector Based on Affine Projection Approach

The Algorithm for Blind Multi-User Detector Based on Affine Projection Approach

Structural-information-awareness-based regularization model for infrared image stripe noise removal

Contact Info

Product

Resources

About