Noise vs Feature: Probabilistic Denoising of Time-of-Flight Range Data
نویسنده
چکیده
Advances in active 3D range sensors have enabled the recording of depth maps at video frame rates. Unfortunately, the captured depth data is often noticeably contaminated with noise. We present a series of statistical analyses and denoising techniques to improve the raw output of depth sensors. Unifying our investigations is the concept that in the presence of high sensor noise, the ability to distinguish effectively between noise corruption and real depth features is needed to reconstruct the original true geometry realistically.
منابع مشابه
A Bayesian approach for image denoising in MRI
Magnetic Resonance Imaging (MRI) is a notable medical imaging technique that is based on Nuclear Magnetic Resonance (NMR). MRI is a safe imaging method with high contrast between soft tissues, which made it the most popular imaging technique in clinical applications. MR Imagechr('39')s visual quality plays a vital role in medical diagnostics that can be severely corrupted by existing noise duri...
متن کاملDenoising of continuous-wave time-of-flight depth images using confidence measures
Abstract Time-of-flight range sensors with on-chip continuous-wave correlation of radio frequency modulated signals are increasingly popular. They simultaneously deliver depth maps and intensity images with noise and systematic errors that are unique for this particular kind of data. Based on recent theoretical findings on the dominating noise processes we propose specific variants of normalize...
متن کاملClassification of ECG signals using Hermite functions and MLP neural networks
Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. In the first module the stationary wavelet transform (SWF) is used for noise reduction of ...
متن کاملStatistical Wavelet-based Image Denoising using Scale Mixture of Normal Distributions with Adaptive Parameter Estimation
Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the MAP estimator depends on the proposed model for noise-free wavelet coefficients. Thus in the wa...
متن کاملApplication of Single-Frequency Time-Space Filtering Technique for Seismic Ground Roll and Random Noise Attenuation
Time-frequency filtering is an acceptable technique for attenuating noise in 2-D (time-space) and 3-D (time-space-space) reflection seismic data. The common approach for this purpose is transforming each seismic signal from 1-D time domain to a 2-D time-frequency domain and then denoising the signal by a designed filter and finally transforming back the filtered signal to original time domain. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008