Image de-noising is one of the fundamental problems in the field of image processing needed for improving the image quality before performing different high-level vision tasks. Numerous wavelet based denoising methods were utilized for performing image de-noising process. In such works, there is a lack of analysis in selecting the appropriate threshold value. Moreover, such analysis leads to th...

The existence of noise has great influence on the real features of observed time series, thus noise reduction in time series data is a necessary and significant task in many practical applications. When using traditional de-noising methods, the results often cannot meet the practical needs due to their inherent shortcomings. In the present paper, first a set of key but difficult wavelet de-nois...

The rope-less elevator driven by Permanent Magnet Linear Synchronous Motor (PMLSM) is a new technology for high-rise buildings. In the practical operation, PMLSM inevitably encounters various kinds of turbulences which directly affect the rope-less elevator’s operation. The braking system is important for rope-less elevator safe and steady operation. Usually, the ordinary inspections are not ab...

This paper presents a novel hybrid algorithm based on particle swarm optimization (PSO) and noising metaheuristics for solving the single-source shortest-path problem (SPP) commonly encountered in graph theory. This hybrid search process combines PSO for iteratively finding a population of better solutions and noising method for diversifying the search scheme to solve this problem. A new encodi...

Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise i...

Here it is represented an image analysis technique using both noising & de-noising process. By taking a simple image of different formats we added a noise i. e. Gaussian noise to the particular image and then the calculation of SNR(SIGNAL-TO-NOISE RATIO) and PSNR(PEAK SIGNAL-TO-NOISE RATIO) is performed based on the image formats such as jpeg, png, etc. Although there are various types of noise...

De-noising is one of the most important applications of image processing which has been applied to a wide variety of real world problems. De-noising allows for improving image quality in imaging modalities that are noise prone. A lot of research work has gone in to improving quality of 2D images using various de-noising techniques but new modalities of imaging such as industrial 3D X-ray comput...

The use of electrocardiogram (ECG) plays significant role in the diagnosis of heart disease and human computer interface etc. But, the ECG signals get affected from different types of noise during data acquisition due to which it faces the problem to detect actual abnormality. De-noising of the ECG signal is so indispensable and for de-noising it various researcher work in this area. In this wo...

Cryo-Electron Tomography is a leading imaging technique in structural biology, which is capable of acquiring two-dimensional projections of cellular structures at high resolution and close-to-native state. Due to the limited electron dose the resulting projections exhibit extremely low SNR and contrast. The 3D structure is then reconstructed and passed through a number of post-processing steps ...

seismic waves are non-stationary due to its propagation through the earth. time-frequency transformsare suitable tools for analyzing non-stationary seismic signals. spectral decomposition can reveal thenon-stationary characteristics which cannot be easily observed in the time or frequency representationalone. various types of spectral decomposition methods have been introduced by some researche...