|Table of Contents|

Cross-modal Filter with Joint Spatiality Adaptive Means(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2022年01期
Page:
52-58
Research Field:
机器学习
Publishing date:

Info

Title:
Cross-modal Filter with Joint Spatiality Adaptive Means
Author(s):
Du Wanjun1; 2; Sun Zhonggui2
(1.Ji Xianlin Honors School,Liaocheng University,Liaocheng 252000,China)(2.School of Mathematical Sciences,Liaocheng University,Liaocheng 252000,China)
Keywords:
non-local means; spatiality adaptation; depth image; cross-modality
PACS:
TP391.41
DOI:
10.3969/j.issn.1672-1292.2022.01.008
Abstract:
Non-local means filter uses Euclidean distance to measure the similarity of gray values between pixel blocks in a non-local area. In this sense,the filter does not take the locality into account,and thus leads to several local and aperiodic details being over smoothed in denoising process. To address this problem,this work pursues a local and non-local adaptive strategies to improve the performance of non-local means filter. Meanwhile,considering the fact that multi-modal images are widely used in practice,we also focus on extending non-local means filter to a cross-modal version. Finally,a novel filter is achieved which is cross-modal and can adaptively tradeoff between local and non-local implementation. Experimental results show that the performance of the proposed method is more powerful than the original one.

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Last Update: 2022-03-15