In this paper, a new adaptive coefficient scanning scheme, which is called local- and global-prediction-based adaptive scanning (LGPAS), is described to improve the coding efficiency of discrete ...cosine transform (DCT)-based image compression methods including JPEG and H.264/AVC intra-coding, in which zigzag scanning is used. The coding performance is limited because the zigzag scan order ignores the statistical properties of the DCT coefficients. On the other hand, we adopt not only the global information but also the local information to perform learning and adaptively generate the scanning patterns, unlike the existing methods. Furthermore, we adopt variation prediction, nonzero probability estimation, and the proposed techniques of zigzag weighting and energy weighting matrices to generate the scanning pattern. On the basis of the local and global predictions for the probability distributions of the nonzero DCT coefficients in an image, the proposed LGPAS scheme can adaptively update the scan order patterns and thus achieves a higher entropy coding gain. Simulations show that the proposed scheme significantly outperforms the conventional zigzag scanning method and other existing adaptive scanning methods.
In this paper, a very efficient image denoising scheme, which is called nonlocal means based on bidirectional principal component analysis, is proposed. Unlike conventional principal component ...analysis (PCA) based methods, which stretch a 2D matrix into a 1D vector and ignores the relations between different rows or columns, we adopt the technique of bidirectional PCA (BDPCA), which preserves the spatial structure and extract features by reducing the dimensionality in both column and row directions. Moreover, we also adopt the coarse-to-fine procedure without performing nonlocal means iteratively. Simulations demonstrated that, with the proposed scheme, the denoised image can well preserve the edges and texture of the original image and the peak signal-to-noise-ratio is higher than that of other methods in almost all the cases.
One of the most important applications of the wireless sensor networks is the widely applied smart environment. To prolong the network lifetime, it is important to develop the protocols for reducing ...energy consumption because the sensor nodes are constrained by limited energy. In the cluster based on energy-efficient method, the fixed cluster head number, the energy of the node, and the transmission distance are the keys to extending the network lifetime. In this paper, we propose an improved grouping protocol, which considers the distance between the sensor node and the sink node in order to allocate total energy of a group. The proposed method is compared with previous works of simulations to show the advantages of extending the network lifetime.
In this paper, a new adaptive scanning scheme, which is called local prediction based adaptive scanning (LPBAS), is proposed for discrete cosine transform (DCT) based image compression techniques ...including JPEG and H.264/AVC intra coding. The conventional zigzag scan order is widely used in image and video coding standards, but it ignores the statistical properties of DCT blocks and has limited performance. In this paper, the LPBAS scheme is proposed to achieve the entropy coding gain, where the scan order patterns are adaptively generated and updated based on the statistics of local neighboring DCT blocks. The proposed scheme improves the efficiency of the two image coding systems, JPEG and the H.264/AVC intra coding system. Simulation results showed that the proposed scheme indeed outperforms the zigzag scanning method and other existing adaptive scanning methods.
A method of natural image classification by an effective color quadtree segmentation together with a more effective codebook with the color local thresholding classifier for content-based image ...retrieval (CBIR) is proposed. The vector quantization (VQ) based image retrieval schemes have good performance, but the importance of color edge intensive blocks is neglected. Our proposed method has two main improvements. First, quadtree segmentation based on both hue and gray-level information is applied to classify the blocks into the homogeneous and high-detail ones. Second, a color local thresholding classifier is proposed to further classify the high-detail blocks based on edge information. Simulation results show that our proposed scheme outperforms the existing methods, including the Quadtree CVQ-based scheme, the VQ-based scheme, and other methods.
Telehealth care is a global trend affecting clinical practice around the world. To mitigate the workload of health professionals and provide ubiquitous health care, a comprehensive surveillance ...system with value-added services based on information technologies must be established.
We conducted this study to describe our proposed telesurveillance system designed for monitoring and classifying electrocardiogram (ECG) signals and to evaluate the performance of ECG classification.
We established a telesurveillance system with an automatic ECG interpretation mechanism. The system included: (1) automatic ECG signal transmission via telecommunication, (2) ECG signal processing, including noise elimination, peak estimation, and feature extraction, (3) automatic ECG interpretation based on the support vector machine (SVM) classifier and rule-based processing, and (4) display of ECG signals and their analyzed results. We analyzed 213,420 ECG signals that were diagnosed by cardiologists as the gold standard to verify the classification performance.
In the clinical ECG database from the Telehealth Center of the National Taiwan University Hospital (NTUH), the experimental results showed that the ECG classifier yielded a specificity value of 96.66% for normal rhythm detection, a sensitivity value of 98.50% for disease recognition, and an accuracy value of 81.17% for noise detection. For the detection performance of specific diseases, the recognition model mainly generated sensitivity values of 92.70% for atrial fibrillation, 89.10% for pacemaker rhythm, 88.60% for atrial premature contraction, 72.98% for T-wave inversion, 62.21% for atrial flutter, and 62.57% for first-degree atrioventricular block.
Through connected telehealth care devices, the telesurveillance system, and the automatic ECG interpretation system, this mechanism was intentionally designed for continuous decision-making support and is reliable enough to reduce the need for face-to-face diagnosis. With this value-added service, the system could widely assist physicians and other health professionals with decision making in clinical practice. The system will be very helpful for the patient who suffers from cardiac disease, but for whom it is inconvenient to go to the hospital very often.
Pitch estimation is to estimate the fundamental frequency and the midi number and plays a critical role in music signal analysis and vocal signal processing. In this work, we proposed a new ...architecture based on a learning-based enhancement preprocessor and a combination of several traditional and deep learning pitch estimation methods to achieve better pitch estimation performance in both noisy and clean scenarios. We test 17 different types of noise and 4 SNR db noise levels. The results show that the proposed pitch estimation can perform better in both noisy and clean scenarios with short response time.
Dynamic programming (DP) is an effective algorithm to determine the similarity between two sequences. It plays an important role in text comparison, nucleotide sequence alignment, and melody ...matching. Conventional DP method performs element-to-element or element-to-space comparison and considers only the cases of replacement, deletion, and insertion. In this work, we improve the DP method by performing multiple element comparison. That is, in addition to perform element-wise comparison, we also compare the similarities of element-space to element and space-element to element. Moreover, the global similarity is also adopted to improve the accuracy of DP. Experiments show that, with the proposed algorithm, the accuracy of melody matching can be much improved. It is helpful for improving the performance of the query-by-humming system and applicable to other sequence comparison problems.
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