Multiresolution analysis

About: Multiresolution analysis is a research topic. Over the lifetime, 4032 publications have been published within this topic receiving 140743 citations. The topic is also known as: Multiresolution analysis, MRA.

Pansharpening With Multiscale Normalized Nonlocal Means Filter: A Two-Step Approach

Abstract: Pansharpening aims to synthesize a high-spatial-resolution multispectral (MS) image by fusing a panchromatic (PAN) image and a low-resolution MS image. The multiresolution analysis (MRA)-based methods are a popular group of pansharpening methods. However, in the MRA-based methods, spatial distortions may occur in the pansharpened product due to the misalignment of PAN and MS data. To address the spatial distortion issue in MRA-based methods, this paper proposes a two-step approach, which consists of the coarse step and the refined step. The coarse step produces a preliminary result using the traditional details injection model. Then, the preliminary product is refined with a second details injection operation in the refined step. Moreover, in our proposed two-step approach, a novel multiscale decomposition based on a normalized nonlocal means (NNLM) filter is developed to extract the spatial detail. Compared with the original nonlocal means filter, the designed NNLM makes the similarity measure more robust and accurate by exploiting the normalized intensity value and the mean value jointly. The experimental results on various satellite data demonstrate the superiority of the proposed pansharpening scheme by comparing with ten well-known methods.

Multiresolution analysis as an approach for tool path planning in NC machining

Abstract: Wavelets permit multiresolution analysis of curves and surfaces. A complex curve can be decomposed using wavelet theory into lower resolution curves. The low-resolution (coarse) curves are similar to rough-cuts and high-resolution (fine) curves to finish cuts in NC machining. In this paper, we investigate the applicability of multiresolution analysis using B-spline wavelets to NC machining of contoured 2D objects. High-resolution curves are used close to the object boundary similar to conventional offsetting while lower resolution curves are used farther away from the object boundary. Experimental results indicate that wavelet-based tool path planning improves machining efficiency. Tool path length is reduced, sharp corners are smoothed out thereby reducing uncut areas and larger tools can be selected for rough-cuts.

Time-of-flight depth image denoising using prior noise information

Abstract: In this paper, we propose a novel way of using time-of-flight camera depth and amplitude images to reduce the noise in depth images with prior knowledge of spatial noise distribution, which is correlated with the incident light falling on each pixel. The denoising is done in wavelet space and the influence and implications of the extended noise model to wavelet space and common denoising methods are shown.

An introduction to discrete finite frames

Abstract: The frame concept was first introduced by Duffin and Schaeffer (1952), and it is widely used today to describe the behavior of vectors for signal representation. The Gabor (1946) expansion and wavelet transform are two special well-known cases. The goal of this article is to describe the frame theory and introduce a simple tutorial method to find discrete finite frame operators and their frame bounds. An easily implementable method for finding the discrete finite frame and subframe operators has been presented by Kaiser (1994). We introduce the method of Kaiser to compute the discrete finite frame operator. Using subframe operators, the biorthogonal basis and projection vectors in a subspace can be easily calculated. Gabor and wavelet analysis are two popular tools for signal processing, and they can reveal time-frequency distribution for a nonstationary signal. Both schemes can be regarded as signal decompositions onto a set of basis functions, and their basis functions are derived from a single prototype function through simple operations. Therefore, the basis functions used in Gabor and wavelet analysis can be regarded as special frames. For completeness we also make some simple introductions on the results of special frames such as discrete Gabor and wavelet analysis.