Improving MPEG-4 coding performance by jointly optimising compression and blocking effect elimination

Centre for Multimedia Signal Processing, Department of Electronic and Information EngineeringAccepted ManuscriptPublishe

Color quantization of compressed video sequences

Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Optimizing MPEG-4 coding performance by taking post-processing into account

Centre for Multimedia Signal Processing, Department of Electronic and Information EngineeringRefereed conference paper2000-2001 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

A fast two-stage OMP algorithm for coding stereo image residuals

Centre for Multimedia Signal Processing, Department of Electronic and Information EngineeringRefereed conference paper2003-2004 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Traffic crashes at toll plazas in Hong Kong

Poisson regression was used to identify the significant contributory factors to traffic crashes at toll plaza areas in Hong Kong. Information on the crash incidences and traffic volume at the toll plaza areas of ten tolled roads in Hong Kong during 1998-2003 were obtained from the traffic accident database system and annual traffic census of the Transport Department of the Government of Hong Kong Special Administrative Region. These data, together with the geometric and operational characteristics, including toll plaza width, carriageway width, degree of road curvature, road gradient, and toll booth configuration, were incorporated into two aggregated crash predictive models for different traffic directions. The results revealed that the crash likelihood of inbound traffic was increased significantly with downward slope and the crash likelihood of outbound traffic increased with the degree of road curvature.published_or_final_versio

Multiclass segmentation based on generalized fuzzy Gibbs random fields

The model of Gibbs random fields is widely applied to Bayesian segmentation due to its best property of describing the spatial constraint information. However, the general segmentation methods, whose model is defined only on hard levels but not on fuzzy set, may come across a lot of difficulties, e.g., getting the unexpected results or even nothing, especially when the blurred or degraded images are considered. In this paper, two multiclass approaches, based on the model of piecewise fuzzy Gibbs random fields (PFGRF) and that of generalized fuzzy Gibbs random fields (GFGRF) respectively, are presented to address these difficulties. In our experiments, both magnetic resonance image and simulated image are implemented with the two approaches mentioned above and the classical 'hard' one. These three different results show that the approach of GFGRF is an efficient and unsupervised technique, which can automatically and optimally segment the images to be finer.published_or_final_versio

The Efficacy and Cost-Effectiveness of Stepped Care Prevention and Treatment for Depressive and/or Anxiety Disorders: A Systematic Review and Meta-Analysis

published_or_final_versio

Multiple endocrine neoplasia type 2B in a Chinese patient

Multiple endocrine neoplasia type 2B syndrome is rarely reported in Chinese patients. A 25-year-old Chinese male presented with full-blown clinical features of this syndrome, including bilateral phaeochromocytomas, medullary thyroid carcinoma, and characteristic phenotypic features. One-stage surgical treatment was performed and subsequent genetic analysis confirmed a point mutation at codon 918 in exon 16 of the RET proto-oncogene. The mutation was arising de novo as there was no corresponding mutation found in both this parents or younger sister. Data published to date suggest there is no difference in the genetic and pathophysiologic basis, nor clinical characteristics of multiple endocrine neoplasia type 2B in Chinese patients. As the disease can be lethal, early diagnosis by prompt recognition of the characteristic phenotypic features followed by surgical treatment should improve the outcome. Family screening is essential to identify at-risk family members for prophylactic treatment.published_or_final_versio

Brain tumor boundary detection in MR image with generalized fuzzy operator

Boundary detection in MR image with brain tumor is an important image processing technique applied in radiology for 3D reconstruction. The nonhomogeneities density tissue of the brain with tumor can result in achieving the inaccurate location in any boundary detection algorithms. Recently, some studies using the contour deformable model with regional base technique, the performance is insufficient to obtain the fine edge in the tumor, and the considerable error in accuracy is existed. Moreover, even in some of the normal tissue region, edge created by this method has also been encompassed. In this paper, we propose a new approach to detect the boundary of brain tumor based on the generalized fuzzy operator (GFO). One typical example is used for evaluating this method with the contour deformable model.published_or_final_versio

Thyroid cancer cells boundary location by a fuzzy edge detection method

Morphometric assessment of tumor cells is important in the prediction of biological behavior of thyroid cancer. In order to automate the process, the computer-based system has to recognize the boundary of the cells. Many methods for the boundary detection have appeared in the literature and some of them applied to microscopic slice analysis. However, there is no reliable method since the gray-levels in the nuclei are uneven and are similar to the background. In the paper, a fuzzy edge detection method is used and is based on an improved generalized fuzzy operator. The method enhances the nuclei and effectively separates the cells from the background.published_or_final_versio