This paper presents the method for automatic recognition of defects in aircraft riveted joints. The proposed method consists of three steps: pre-processing, feature extraction and classification. Feature extraction wa...
详细信息
The work is aimed on the development of advanced algorithms for analyzing the photoplethysmogram signal, which characterizes cardiac activity. We have designed an algorithm that separates individual pulse waveforms fr...
The work is aimed on the development of advanced algorithms for analyzing the photoplethysmogram signal, which characterizes cardiac activity. We have designed an algorithm that separates individual pulse waveforms from the photoplethysmogram, even in the presence of artifacts caused by pathological changes in zebrafish cardiac activity, due to cadmium exposure. The proposed algorithm is based on digital imageprocessing and discrete wavelet transform; it enables reliable separation of individual pulse waveforms. The data obtained can then be processed using conventional techniques, providing accurate pulse wave characteristics for various applications, including toxicology studies, drug development and developmental biology research.
imageprocessing related to noise suppression may entail partial distortion of useful visual information caused by filtering. Preservation of contours and texture details in the process of image denoising is one of th...
imageprocessing related to noise suppression may entail partial distortion of useful visual information caused by filtering. Preservation of contours and texture details in the process of image denoising is one of the important problems of computer vision. Recent years deep neural networks are widely applied in the tasks of noise suppression and signal recovering. However, neural networks are subjects to spectral bias towards low-frequency components. It results in blurring of contours and local high-frequency details after filtration. We propose loss function based on using high-frequency information of wavelet representation of images during network training to solve the problem. Our experiments demonstrate that this approach improves results of filtration in terms of signal to noise ratio and structural similarity index.
The use of magnetic resonance (MR) image has become more significant when treating rectal cancer. Rectal cancer can be staged more accurately with MRI, which serves as a great tool for choosing the most suitable cours...
详细信息
Discrete wavelet Transformation based watermarking algorithm gives robust, secure and strong results in non-blind and semi blind applications. High coefficients are selected in wavelet transform and binary image embed...
详细信息
ISBN:
(数字)9781665469487
ISBN:
(纸本)9781665469487
Discrete wavelet Transformation based watermarking algorithm gives robust, secure and strong results in non-blind and semi blind applications. High coefficients are selected in wavelet transform and binary image embedded into cover image as a watermark using secret key. Most of embedding algorithms use scaling factor a which is selected by try and use method. In this work, we use flexible scaling factor in different bands of the wavelet and also 8x8 blocks of the cover image to improve performance of the watermarking. Experimental results show that block and flexible scaling factor base wavelet watermarking gives better peak signal-to-noise ratio (PSNR) values in Lena, Barbara, peppers and cameraman images. In addition to that, extracted logo has very high similarity ratio (SR) if compared to other wavelet algorithms. Proposed algorithm is resist against the all common type of attacks.
Deep Compressed Sensing (DCS) has attracted considerable interest due to its superior quality and speed compared to traditional CS algorithms. However, current approaches employ simplistic convolutional downsampling t...
详细信息
ISBN:
(纸本)1577358872
Deep Compressed Sensing (DCS) has attracted considerable interest due to its superior quality and speed compared to traditional CS algorithms. However, current approaches employ simplistic convolutional downsampling to acquire measurements, making it difficult to retain high-level features of the original signal for better image reconstruction. Further-more, these approaches often overlook the presence of both high- and low-frequency information within the network, despite their critical role in achieving high-quality reconstruction. To address these challenges, we propose a novel MultiCross Sampling and Frequency Division Network (MCFD-Net) for image CS. The Dynamic Multi-Cross Sampling (DMCS) module, a sampling network of MCFD-Net, incorporates pyramid cross convolution and dual-branch sampling with multi-level pooling. Additionally, it introduces an atten-tion mechanism between perception blocks to enhance adaptive learning effects. In the second deep reconstruction stage, we design a Frequency Division Reconstruction Module (FDRM). This module employs a discrete wavelet transform to extract high- and low-frequency information from images. It then applies multi-scale convolution and self-similarity attention compensation separately to both types of information before merging the output reconstruction results. The MCFD-Net integrates the DMCS and FDRM to construct an end-to-end learning network. Extensive CS experiments conducted on multiple benchmark datasets demonstrate that our MCFDNet outperforms state-of-the-art approaches, while also exhibiting superior noise robustness. The code is available at ***/songhp/MCFD-Net.
image is an important information-bearing medium with many important attributes. If the image data is released directly, personal privacy will be compromised. This paper aims at how to use the method of differential p...
详细信息
ISBN:
(纸本)9783030967727;9783030967710
image is an important information-bearing medium with many important attributes. If the image data is released directly, personal privacy will be compromised. This paper aims at how to use the method of differential privacy to protect the privacy of image data and make the image data have high usability. In this paper, a WIP method based on wavelet change is proposed. Firstly, wavelet transform is used to compress the image. Then, noise is added to the main features after transformation to obtain the published image satisfying the differential privacy. It solves the problem of low usability of large images and the problem that Fourier transform cannot deal with abrupt signal. Experimental results show that compared with similar methods in the frequency domain, the denoised image obtained by the proposed WIP method is more distinguishable and the information entropy is closer to the original image. The accuracy is 10% higher than other methods. Compared with other frequency-domain methods for image differential privacy protection, the proposed WIP method has higher usability and robustness.
With the innovation and progress of data analysis, human action recognition has become a significant research direction with broad applications in many situations. We propose a skeleton temporal graph (STG) based on g...
详细信息
This paper presents a new method for light field applications such as content replacement and fusion in the gradient domain. This approach is inspired by successful gradient domain based image and video editing techni...
详细信息
This paper presents a new method for light field applications such as content replacement and fusion in the gradient domain. This approach is inspired by successful gradient domain based image and video editing techniques. A necessary and important part of gradient-based solutions is recovering the signal of interest from artificially generated, and typically non-integrable, gradient data. As such, a new algorithm is developed to reconstruct a light field from a given gradient data set. In the algorithm, first, the 4D Haar wavelet decomposition of the light field is obtained from the given gradient data. Then, the light field is obtained from a wavelet synthesis step. This algorithm is intended as a building block for gradient-based light field editing methods, and as such, its performance is analysed on a set of benchmark light field data sets. The proposed reconstruction algorithm is an essential part in developing solutions for two light field problems: light field editing and light field fusion. Results show that processing light fields in the gradient domain offers significant advantages over processing in the intensity domain.
In recent years, with the introduction and development of vehicle-to-everything (v2X) and child presence detection (CPD), there's an increasing demand for in-vehicle perception systems. Millimeter-wave (mmWave) ra...
详细信息
暂无评论