Paper Title:
Multiresolution Non-Local Mean Filter for Infrared Dim and Small Target Background Suppression
  Abstract

Structured clouds and ground building background suppression are difficult problems for dim and small target detection technique. In this paper, the dim and small target background suppression method based on combined curvelet transform with modified non-local means filter was presented to solve the problem. And local gradient statistics is introduced to boost ability of method which suppresses false by background structure. The innovation was that the curvelet transform was adopted to decompose the input infrared image, which extracts multi-scale and directional detail features of the image. Moreover non-local means filter improved by local gradient characteristic was introduced to suppress background details and enhance target information for suppression background. Compared with two-dimensional least mean square (TDLMS) and modified partial differential equation (MPDE) methods, through visual quality and value index, several groups of experimental results demonstrate that the presented method can suppress complicated background in dim and small target image effectively.

  Info
Periodical
Chapter
Chapter 6: Energy & Electronic
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
637-642
DOI
10.4028/www.scientific.net/AMM.135-136.637
Citation
J. Li, J. Chang, H. L. Qin, "Multiresolution Non-Local Mean Filter for Infrared Dim and Small Target Background Suppression", Applied Mechanics and Materials, Vols. 135-136, pp. 637-642, 2012
Online since
October 2011
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Price
$32.00
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