Sonar target enhancement by shrinkage of incoherent wavelet coefficients.

نویسندگان

  • Alan J Hunter
  • Robbert van Vossen
چکیده

Background reverberation can obscure useful features of the target echo response in broadband low-frequency sonar images, adversely affecting detection and classification performance. This paper describes a resolution and phase-preserving means of separating the target response from the background reverberation noise using a coherence-based wavelet shrinkage method proposed recently for de-noising magnetic resonance images. The algorithm weights the image wavelet coefficients in proportion to their coherence between different looks under the assumption that the target response is more coherent than the background. The algorithm is demonstrated successfully on experimental synthetic aperture sonar data from a broadband low-frequency sonar developed for buried object detection.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multiresolution Markov Random Field Wavelet Shrinkage for Ripple Suppression in Sonar Imagery

A recent dual-tree wavelet shrinkage method to suppress sand ripples in sonar imagery is extended with a Markov random field framework. Markov chain Monte Carlo sampling is used to estimate the posterior marginal ripple state in the wavelet domain. Ripple suppression is realised by multiplying the dual-tree wavelet coefficients by the conditional probabilities of the non-ripple state. Tests on ...

متن کامل

A New Method for Speech Enhancement Based on Incoherent Model Learning in Wavelet Transform Domain

Quality of speech signal significantly reduces in the presence of environmental noise signals and leads to the imperfect performance of hearing aid devices, automatic speech recognition systems, and mobile phones. In this paper, the single channel speech enhancement of the corrupted signals by the additive noise signals is considered. A dictionary-based algorithm is proposed to train the speech...

متن کامل

Fuzzy Shrink Thresholding based Tea Leaf Image Enhancement using Wavelet Transform

In this paper a wavelet shrinkage algorithm based on fuzzy logic is proposed to improve the tea leaf image. The Tea Leaf images are normally changes to unclear images by the presence of noise, low or high dissimilarity both in the edge area and also in the image area. The Fuzzy shrink is used to enhance the image. In exacting, intra-scale dependency within wavelet coefficients is modeled using ...

متن کامل

Target detection in side-scan sonar images: expert fusion reduces false alarms

We integrate several key components of a pattern recognition system for a mine-like targets detection problem. These include several image enhancements, postprocessing and multi-expert fusion. The image enhancement includes wavelet de-noising and classical computer vision methods such as nonlinear and adaptive equalization and other filters. Our approach attempts to make the different experts a...

متن کامل

Bayesian Wavelet Shrinkage

Bayesian wavelet shrinkage methods are defined through a prior distribution on the space of wavelet coefficients after a Discrete Wavelet Transformation has been applied to the data. Posterior summaries of the wavelet coefficients establish a Bayes shrinkage rule. After the Bayes shrinkage is performed, an Inverse Discrete Wavelet Transformation can be used to recover the signal that generated ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • The Journal of the Acoustical Society of America

دوره 135 1  شماره 

صفحات  -

تاریخ انتشار 2014