We have investigated an original motion estimation method that exploits several frequency subbands of wavelet pyramids using a multigrid-multiconstraint strategy. A recursive and iterative solution based on the Wiener approach allows to take into account the reconstruction quality criterion that is crucial to image coding. Experiments show its performances in terms of compression ratio, reconstruction quality, and reduction of implementation complexity compared to a monoresolution case.
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http://dx.doi.org/10.1109/83.334975 | DOI Listing |
Bioengineering (Basel)
December 2024
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
In recent years, image-guided brachytherapy for cervical cancer has become an important treatment method for patients with locally advanced cervical cancer, and multi-modality image registration technology is a key step in this system. However, due to the patient's own movement and other factors, the deformation between the different modalities of images is discontinuous, which brings great difficulties to the registration of pelvic computed tomography (CT/) and magnetic resonance (MR) images. In this paper, we propose a multimodality image registration network based on multistage transformation enhancement features (MTEF) to maintain the continuity of the deformation field.
View Article and Find Full Text PDFOphthalmol Sci
August 2024
Kellogg Eye Center, Department of Ophthalmology & Visual Sciences, University of Michigan, 1000 Wall Street, Ann Arbor, Michigan, 48105.
Purpose: Pupillary instability is a known risk factor for complications in cataract surgery. This study aims to develop and validate an innovative and reliable computational framework for the automated assessment of pupil morphologic changes during the various phases of cataract surgery.
Design: Retrospective surgical video analysis.
ISA Trans
November 2024
College of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, PR China. Electronic address:
In order to realize high-precision diagnosis of bearings faults in a multi-sensor detection environment, a fault diagnosis method based on two-stage signal fusion and deep multi-scale multi-sensor networks is proposed. Firstly, the signals are decomposed and fused using weighted empirical wavelet transform to enhance weak features and reduce noise. Secondly, an improved random weighting algorithm is proposed to perform a second weighted fusion of the signals to reduce the total mean square error.
View Article and Find Full Text PDFSensors (Basel)
July 2024
Department of Oceanography and Hydrography, Dalian Naval Academy, Dalian 116018, China.
Aiming at the problem of low accuracy of multi-scale seafloor target detection in side-scan sonar images with high noise and complex background texture, a model for multi-scale target detection using the BES-YOLO network is proposed. First, an efficient multi-scale attention (EMA) mechanism is used in the backbone of the YOLOv8 network, and a bi-directional feature pyramid network (Bifpn) is introduced to merge the information of different scales, finally, a Shape_IoU loss function is introduced to continuously optimize the model and improve its accuracy. Before training, the dataset is preprocessed using 2D discrete wavelet decomposition and reconstruction to enhance the robustness of the network.
View Article and Find Full Text PDFNeural Netw
October 2024
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore. Electronic address:
Recently, multi-resolution pyramid-based techniques have emerged as the prevailing research approach for image super-resolution. However, these methods typically rely on a single mode of information transmission between levels. In our approach, a wavelet pyramid recursive neural network (WPRNN) based on wavelet energy entropy (WEE) constraint is proposed.
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