• Journal of the Korean association of regional geographers
• /
• v.22 no.1
• /
• pp.251-266
• /
• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.5
• /
• pp.155-164
• /
• 2015

This paper describes a design and implementation of CABAC decoder, which would handle HEVC syntax elements in adaptively pipelined-parallel computation manner. Even though CABAC offers the high compression rate, it is limited in decoding performance due to context-based sequential computation, and strong data dependency between context models, as well as decoding procedure bin by bin. In order to enhance the decoding computation of HEVC CABAC, the flag-type syntax elements are adaptively pipelined by precomputing consecutive flag-type ones; and multi-bin syntax elements are decoded by processing bins in parallel up to three. Further, in order to accelerate Binary Arithmetic Decoder by reducing the critical path delay, the update and renormalization of context modeling are precomputed parallel for the cases of LPS as well as MPS, and then the context modeling renewal is selected by the precedent decoding result. It is simulated that the new HEVC CABAC architecture could achieve the max. performance of 1.01 bins/cycle, which is two times faster with respect to the conventional approach. In ASIC design with 65nm library, the CABAC architecture would handle 224 Mbins/sec, which could decode QFHD HEVC video data in real time.

• Journal of Internet Computing and Services
• /
• v.16 no.1
• /
• pp.29-37
• /
• 2015

In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.