• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1025-1031
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• 2006

In this paper, a deconvolution filtering method for all-pass systems based on FIR approximation is proposed. The proposed method enables us to obtain a causal stable deconvolution filter by FIR approximating a non-causal stable deconvolution filter to a causal stable one. As we can see in this paper, the impulse response of the deconvolution filter for all-pass system is simply the mirror image of the impulse response for all-pass system itself. Due to this symmetric property between all-pass system itself and its deconvolution Inter, this method can be applied to all-pass systems without special limitation of the system's order. In order to verify the performance of the proposed method. computer simulation results for 1st-, 2nd- and 400th-order all-pass systems are included.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• pp.166-171
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• 2001

A digital seismic data acquisition and processing system using a PC has been developed in order to replace the analog data acquisition system of shallow marine seismic survey. An A/D converter that has 12bits of resolution and 225KHz of conversion rate was ued to acquire data, and a data acquisition software was developed as a Windows program which provides convenience of use. Raw data acquired at field has been saved to the hard-disk simultaneously. The signal to noise ratio, vertical and horizontal resolution could be improved by a digital data processing of the raw data. The digital processing of the raw data includss gain recovery, filtering, deconvolution, and muting. With the prediction deconvolution algorithm multiple reflections appearing on the shallow marine seismic section could be removed successfully.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.517-524
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• 2011

This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.43-48
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• 2014

Usually, image deconvolution is applied as a preprocessing step in surveillance systems to reduce the effect of motion or out-of-focus blur problem. In this paper, we propose a blind-image deconvolution filtering approach based on genetic programming (GP). A numerical expression is developed using GP process for image restoration which optimally combines and exploits dependencies among features of the blurred image. In order to develop such function, first, a set of feature vectors is formed by considering a small neighborhood around each pixel. At second stage, the estimator is trained and developed through GP process that automatically selects and combines the useful feature information under a fitness criterion. The developed function is then applied to estimate the image pixel intensity of the degraded image. The performance of developed function is estimated using various degraded image sequences. Our comparative analysis highlights the effectiveness of the proposed filter.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.465-473
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• 2018

The application of singular value decomposition (SVD) filtering is examined for attenuation of the ground-roll in land seismic data. Prior to the SVD computation to seek singular values containing the highly correlatable reflection energy, processing steps such as automatic gain control, elevation and refraction statics, NMO correction, and residual statics are performed to enhance the horizontal correlationships and continuities of reflections. Optimal parameters of SVD filtering are effectively chosen with diagnostic display of inverse NMO (INMO) corrected CSP (common shot point) gather. On the field data with dispersion of ground-roll overwhelmed, continuities of reflection events are much improved by SVD filtering than f-k filtering by eliminating the ground-roll with preserving the low-frequency reflections. This is well explained in the average amplitude spectra of the f-k and SVD filtered data. The reflectors including horizontal layer of the reservoir are much clearer on the stack section, with laminated events by SVD filtering and subsequent processing steps of spiking deconvolution and time-variant spectral whitening.

• Journal of Soil and Groundwater Environment
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• v.11 no.3
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• pp.52-58
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• 2006

Kim and Lee (2005) suggested Minimum Entropy Deconvolution (MED) to estimate the temporal sequence of the relative recharge. However this study by Kim and Lee (2005) was just related to the verification of the conceptual approach with MED. In this study, we try to characterize the applicability of MED in the case of spatially heterogeneous recharge (distance from recharge area). Simulated results were recorded with some specific sampling points. Estimated results from this study show higher than 0.8 in cross-correlation with the original recharge sequence. In addition, the physical and mathematical meanings of the applied filter length was also investigated. It was revealed that the length of filter is highly related to the spatial distance between recharge area and the monitoring site, and the apparent shape of hydraulic head change.

• 한국해양학회지
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• v.30 no.2
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• pp.116-124
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• 1995

Marine, shallow seismic data have been acquired and processed by newly developed multi-channel(6 channel), PC-based digital recording and processing system. The digital processing system includes pre-processing, swell-compensation filter, frequency filter, gain correction, deconvolution, stacking, migration, and plotting. The quality of processed sections is greatly enhanced in terms of signal-to-noise ratio and vertical/horizontal resolution. The multi-channel, digital recording, acquisition and processing system proved to be and economical, efficient and easy-to-use marine shallow seismic tool.

• Geophysics and Geophysical Exploration
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• v.12 no.2
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• pp.192-198
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• 2009

Side scan sonar and SBP (sub-bottom profiler) play a very important role in the survey for seafloor imaging and sub-bottom profiling. In this study, we have acquired side scan sonar and SBP data from the artificial reef area. We applied digital image processing techniques to side scan sonar data in order to improve an image quality. For the enhancement of data quality and image resolution, we applied the typical seismic data processing sequence including gain recovery, muting, spectrum analysis, predictive deconvolution, migration to SBP data. We could easily estimate if artificial reef structures were settled properly and their distribution on the seafloor from the integrated interpretation of side scan sonar and SBP data. From the sampling analysis of seabed sediments, texture filtering of side scan sonar data and SBP data interpretation, we could evaluate the sediment type, distribution and thickness of seafloor sediments in detail.

• Proceedings of the IEEK Conference
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• pp.547-550
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• 2001

Through matched filtering synthetic aperture radar (SAR) produces high-resolution imagery from data collected by a relative small antenna. While the impulse response obtained by the matched filter approach produces the best achievable signal-to-noise ratio, large sidelobes must be reduced to obtain higher-resolution SAR images. So, many enhancement methods of SAR imagery have been proposed. As a deconvolution method, the phase-extension inverse filtering is based on the characteristics of the matched filtering used in SAR imaging. It improves spatial resolution as well as effectively suppresses the sidelobes with low computational complexity. In the phase-extension inverse filtering, the impulse response is obtained from simulation with a point target. But in a real SAR environment, for example ERS-1, the impulse response is distorted by many non-ideal factors. So, in the phase-extension inverse filtering for a real SAR processing, the magnitudes of the frequency transfer function have to be compensated to produce more desirable results. In this paper, an estimation method to obtain a more accurate impulse response from a real SAR image is studied. And a compensation scheme to produce better performance of the phase-extension inverse filtering is also introduced.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.77-84
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• 2009

Ground penetrating radar (GPR) is an effective tool for detecting shallow subsurface targets. In many GPR applications, these targets are veiled by the strong waves reflected from the ground surface, so that we need to apply a signal processing technique to separate the target signal from such strong signals. A pulse-compression technique is used in this research to compress the signal width so that it can be separated out from the strong contaminated clutter signals. This work introduces a filter algorithm to carry out pulse compression for GPR data, using a Wiener filtering technique. The filter is applied to synthetic and field GPR data acquired over a buried pipe. The discrimination method uses both the reflected signal from the target and the strong ground surface reflection as a reference signal for pulse compression. For a pulse-compression filter, reference signal selection is an important issue, because as the signal width is compressed the noise level will blow up, especially if the signal-to-noise ratio of the reference signal is low. Analysis of the results obtained from simulated and field GPR data indicates a significant improvement in the GPR image, good discrimination between the target reflection and the ground surface reflection, and better performance with reliable separation between them. However, at the same time the noise level slightly increases in field data, due to the wide bandwidth of the reference signal, which includes the higher-frequency components of noise. Using the ground-surface reflection as a reference signal we found that the pulse width could be compressed and the subsurface target reflection could be enhanced.