• ETRI Journal
• /
• v.32 no.4
• /
• pp.577-587
• /
• 2010

The layered coding structure of scalable video coding (SVC) with adaptive inter-layer prediction causes noticeable computational complexity increments when compared to existing video coding standards. To lighten the computational complexity of SVC, we present a fast algorithm to speed up the inter-mode decision process. The proposed algorithm terminates inter-mode decision early in the enhancement layers by estimating the rate-distortion (RD) cost from the macroblocks of the base layer and the enhancement layer in temporal, spatial, and inter-layer directions. Moreover, a search range decision algorithm is also proposed in this paper to further increase the motion estimation speed by using the motion vector information from temporal, spatial, or inter-layer domains. Simulation results show that the proposed algorithm can determine the best mode and provide more efficient total coding time saving with very slight RD performance degradation for spatial and quality scalabilities.

• Journal of the Korean Geographical Society
• /
• v.40 no.2 s.107
• /
• pp.221-241
• /
• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.5 no.4
• /
• pp.372-378
• /
• 2010

This paper propose the fast motion estimation algorithm with adaptive search range adjustment using motion activities of temporal and spatial neighbor blocks. The existing fast motion estimation algorithms with adaptive search range adjustment use the maximum motion vector of all blocks in the reference frame. So these algorithms may not control a optimum search range for slow moving block in current frame. The proposed algorithm use the maximum motion vector of neighbor blocks in the reference frame to control a optimum search range for slow moving block. So the proposed algorithm can reduce computation time for motion estimation. The experiment results show that the proposed algorithm can reduce the number of search points about 15% more than Simple Dynamic Search Range(SDSR) algorithm while maintaining almost the same bit-rate and motion estimation error.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.7
• /
• pp.1980-1987
• /
• 1999

Restored image is always lower quality than original one due to distortion and noise. The purpose of image restoration is to improve the image quality by fixing the noise or distortion information. One category of spatial filters for image restoration is linear filter. This filter algorithm is easily implemented and can be suppressed the Gaussian noise effectively, but not so good performance for spot or impulse noise. In this paper, we propose the nonlinear spatial filter algorithm for image restoration called the optimal adaptive multistage filter(OAMF). The OAMF is used to reduce the filtering time, increases the noise suppression ratio and preserves the edge information. The OAMF optimizes the adaptive multistage filter(AMF) by using weight learning algorithm of back-propagation learning algorithm. Simulation results of this filter algorithm are presented and discussed.

• Korean Journal of Remote Sensing
• /
• v.18 no.2
• /
• pp.117-125
• /
• 2002

Multitemporal analysis with remotely sensed data is complicated by numerous intervening factors, including atmospheric attenuation and occurrence of clouds that obscure the relationship between ground and satellite observed spectral measurements. Using an adaptive reconstruction system, dynamic compositing approach was developed to recover missing/bad observations. The reconstruction method incorporates temporal variation in physical properties of targets and anisotropic spatial optical properties into image processing. The adaptive system performs the dynamic compositing by obtaining a composite image as a weighted sum of the observed value and the value predicted according to local temporal trend. The proposed system was applied to the sequence of NDVI images of AVHRR observed on the Korean Peninsula from 1999 year to 2000 year. The experiment shows that the reconstructed series can be used as an estimated series with complete data for the observations including bad/missing values. Additionally, the gradient image, which represents the amount of temporal change at the corresponding time, was generated by the proposed system. It shows more clearly temporal variation than the data image series.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2427-2429
• /
• 1998

Digital watermarking is the techinque which embeds the invisible signal into multimedia data such as audio, video, images, for copyright protection, including owner identification and copy control information. This paper proposes a new watermark embedding and extraction technique by extending the direct sequence spread spectrum technique. The proposed technique approximates the frequency component of pixels in spatial domain by using Laplacian mask and adaptively embeds the watermark considering the HVS to reduce the degradation of Image. In watermark extraction process, the proposed technique strengthens the high frequency components of image and extracts the watermark by demodulation. All this processes are performed in spatial domain to reduce the processing time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1996.06a
• /
• pp.223-227
• /
• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• Journal of Communications and Networks
• /
• v.12 no.4
• /
• pp.358-365
• /
• 2010

We develop a low complexity cooperative diversity protocol for low energy adaptive clustering hierarchy (LEACH) based wireless sensor networks. A cross layer approach is used to obtain spatial diversity in the physical layer. In this paper, a simple modification in clustering algorithm of the LEACH protocol is proposed to exploit virtual multiple-input multiple-output (MIMO) based user cooperation. In lieu of selecting a single cluster-head at network layer, we proposed M cluster-heads in each cluster to obtain a diversity order of M in long distance communication. Due to the broadcast nature of wireless transmission, cluster-heads are able to receive data from sensor nodes at the same time. This fact ensures the synchronization required to implement a virtual MIMO based space time block code (STBC) in cluster-head to sink node transmission. An analytical method to evaluate the energy consumption based on BER curve is presented. Analysis and simulation results show that proposed cooperative LEACH protocol can save a huge amount of energy over LEACH protocol with same data rate, bit error rate, delay and bandwidth requirements. Moreover, this proposal can achieve higher order diversity with improved spectral efficiency compared to other virtual MIMO based protocols.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.161-162
• /
• 2011

Recently, many research works are focusing on DVC (Distributed Video Coding) system for low complexity encoder. However the feedback channel-based parity bit control is a major cause of the high decoding time latency. Spatial and temporal correlation is high in video and, therefore, the statistical property can be applied for the parity bit request of LDPCA frame. By introducing frame adaptive parity bit request estimation method, this paper proposes a new method for reducing the decoding time latency. Through computer simulations, it is shown that the proposed method achieves about 80% of complexity reduction, compared to the conventional no-estimation method.

• Journal of KIISE
• /
• v.44 no.11
• /
• pp.1209-1218
• /
• 2017

A variety of sensors is widely used these days, and it has become much easier to acquire spatial big data streams from various sources. Since spatial data streams have inherently skewed and dynamically changing distributions, the system must effectively distribute the load among workers. Previous studies to solve this load imbalance problem are not directly applicable to processing spatial data. In this research, we propose Adaptive Spatial Key Grouping (ASKG). The main idea of ASKG is, by utilizing the previous distribution of the data streams, to adaptively suggest a new grouping scheme that evenly distributes the future load among workers. We evaluate the validity of the proposed algorithm in various environments, by conducting an experiment with real datasets while varying the number of workers, input rate, and processing overhead. Compared to two other alternative algorithms, ASKG improves the system performance in terms of load imbalance, throughput, and latency.