搜索结果: 1-15 共查到“Denoising”相关记录46条 . 查询时间(0.062 秒)
HYPERSPECTRAL IMAGE DENOISING USING A NONLOCAL SPECTRAL SPATIAL PRINCIPAL COMPONENT ANALYSIS
Hyperspectral Images Noise Reduction Nonlocal Similarity Spectral Spatial Information Principal Component Analysis
2018/5/14
Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classi...
UNMIXING-BASED DENOISING AS A PRE-PROCESSING STEP FOR CORAL REEF ANALYSIS
Hyperspectral remote sensing Coral Denoising Water Derivative Features Spectral Unmixing
2017/7/12
Coral reefs, among the world’s most biodiverse and productive submerged habitats, have faced several mass bleaching events due to climate change during the past 35 years. In the course of this century...
CUBESAT-DERIVED DETECTION OF SEAGRASSES USING PLANET IMAGERY FOLLOWING UNMIXING-BASED DENOISING: IS SMALL THE NEXT BIG?
Mediterranean seagrass Posidonia oceanica Planet CubeSats Unmixing-based denoising Depth-invariant index Support Vector Machines
2017/7/12
Seagrasses are one of the most productive and widespread yet threatened coastal ecosystems on Earth. Despite their importance, they are declining due to various threats, which are mainly anthropogenic...
DENOISING ALGORITHM FOR THE PIXEL-RESPONSE NON-UNIFORMITY CORRECTION OF A SCIENTIFIC CMOS UNDER LOW LIGHT CONDITIONS
CMOS Denoising algorithm Pixel-response non-uniformity
2016/7/28
We present a denoising algorithm for the pixel-response non-uniformity correction of a scientific complementary metal–oxide–semiconductor (CMOS) image sensor, which captures images under extremely low...
EVALUATION OF WAVELET AND NON-LOCAL MEAN DENOISING OF TERRESTRIAL LASER SCANNING DATA FOR SMALL-SCALE JOINT ROUGHNESS ESTIMATION
terrestrial laser scanning range noise data resolution joint roughness wavelet transform non-local mean denoising performance
2016/7/27
Terrestrial Laser Scanning (TLS) is a well-known remote sensing tool that enables precise 3D acquisition of surface morphology from distances of a few meters to a few kilometres. The morphological rep...
DENOISING POINT CLOUD DATA OF SMALL-STRUCTURED FREE FORMSURFACES CAPTURED BY A PHASE-BASED LASERSCANNER
Laser scanning Close-range Point Cloud Filtering Cultural Heritage
2016/2/29
Terrestrial laser scanners based on the time-of-flight measurement principle or the phase comparison method are used for cultural
heritage documentation. Only if the scanned surfaces consist of exte...
Terrestrial Laser Scanner Data Denoising by Range Image Processing for Small-Sized Objects
Terrestrial Laser Scanning Denoising Modelling
2015/12/16
The question of 3D data denoising has become a subject of intense research with the development of low cost acquisition systems.
Recent works are based mainly on the adaptation of standard denoising ...
Research and Application of Image Denoising Method Based on Curvelet Transform
IMAGE DENOISING CURVELET SAR APPLICATION
2015/12/2
The images usually bring different kinds of noises in process of receiving, coding and transmission. The curvelet transform is one kind of new multi-scale transform after 1999 that is based on wavelet...
Speckle Denoising Based on Bivariate Shrinkage Functions and Dual-Tree Complex Wavelet Transform
Transformation Algorithms SAR Radiometric Processing, Image
2015/11/20
Bivariate shrinkage functions (bsf) statistically denoted as joint probability density functions (pdf) and noise pdf, can be united by MAP to denoise image. Because the intensity of speckle in synthet...
Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising
Approximate Message Passing Lasso Group Lasso, Joint Sparsity, James- Stein, Minimax Risk over Nearly-Black Objects Minimax Risk of Soft Thresholding Minimax Risk of Firm Thresholding Minimax Shrinkage Nonconvex penalization State Evolution Total Variation Minimization Monotone Regression.
2015/8/21
Compressed sensing posits that, within limits, one can undersample a sparse signal and yet reconstruct it accurately. Knowing the precise limits to such undersampling is important both for theory and ...
Ideal Denoising in an orthonormal basis chosen from a library of bases
Wavelet Packets Cosine Packets weak-` p spaces
2015/8/20
Suppose we have observations yi = si +zi, i = 1; :::; n, where (si) is signal and (zi)
is i.i.d. Gaussian white noise. Suppose we have available a library L of orthogonal
bases, such as the Wavelet ...
Accurate,fast and stable denoising source separation algorithms
denoising source separation DSS independent component analysis ICA blind source separation BSS FastICA stability
2015/7/30
Denoising source separation is a recently introduced framework for building source separation algorithms around denoising procedures. Two developments are reported here. First, a new scheme for accele...
Behaviourally meaningful representations from normalisation and context-guided denoising
Behaviourally meaningful representations normalisation context-guided denoising
2015/7/30
Many existing independent component analysis algorithms include a preprocessing stage where the inputs are sphered. This amounts to normalising the data such that all correlations between the variable...
Denoising source separation
blind source separation BSS prior information denoising denoising source separation DSS independent component analysis ICA magnetoencephalograms MEG CDMA
2015/7/30
A new algorithmic framework called denoising source separation (DSS) is introduced. The main benefit of this framework is that it allows for easy development of new source separation algorithms which ...
The Curvelet Transform for Image Denoising
Radon Transform Wavelets Ridgelets Curvelets FFT FWT Discrete Wavelet Transform Thresholding Rules Filtering
2015/6/17
We describe approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform [3] and the curvelet transform [7, 6]. Our implementations offer exact reconstruction...