This paper describes a highly efficient method for lossless compression of volumetric sets medical images, such as CTs or MRIs. The proposed method, referred to 3-D-MRP, is based on the principle minimum rate predictors (MRPs), which one state-of-the-art technologies presented in data literature. main features include use 3-D predictors, 3-D-block octree partitioning and classification, volume-based optimization, support 16-b-depth images. Experimental results demonstrate efficiency 3-D-MRP...

Light field imaging is a promising new technology that allows the user not only to change focus and perspective after taking picture, as well generate 3D content, among other applications. However, light images are characterized by large amounts of data there lack coding tools efficiently encode this type content. Therefore, paper proposes addition two prediction HEVC framework, improve its efficiency. The first tool based on local linear embedding-based second one self-similarity...

Accurate skin lesion segmentation is important for identification and classification through computational methods. However, when performed by dermatologists, the results of clinical are affected a certain margin inaccuracy (which exists since dermatologist do not delineate lesions but extraction) also significant inter- intra-individual variability, such sufficiently accurate studies. This work addresses these limitations to enable detailed analysis lesions' geometry along with extraction...

Light field imaging technology has been attracting increasing interest because it enables capturing enriched visual information and expands the processing capabilities of traditional 2D systems. Dense multiview, accurate depth maps multiple focus planes are examples different types enabled by light fields. This is also emerging in medical research, like dermatology, allowing to find new features improve classification algorithms, namely those based on machine learning approaches. paper...

Holoscopic imaging is a prospective acquisition and display solution for providing true 3D content fatigue-free visualization. However, efficient coding schemes this particular type of are needed to enable proper storage delivery the large amount data involved in these systems. Therefore, paper proposes an alternative HEVC-based scheme representation holoscopic images. In scheme, some directional intra prediction modes HEVC replaced by more framework based on locally linear embedding...

This paper proposes a two-stage high-order intrablock prediction method for light field image coding. exploits the spatial redundancy in lenslet images by predicting each block, through geometric transformation applied to region of causal encoded area. Light comprise an array microimages that are related complex transformations cannot be efficiently compensated state-of-the-art coding techniques, which usually based on low-order translational models. The nature proposed allows us choose...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this brief, we present new preprocessing techniques for electrocardiogram signals, namely, dc equalization and complexity sorting, which when applied can improve current 2-D compression algorithms. The experimental results with signals from the Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH) database outperform ones many state-of-the-art schemes described in literature. </para>

Intelligent approaches in sports using IoT devices to gather data, attempting optimize athlete’s training and performance, are cutting edge research. Synergies between recent wearable hardware wireless communication strategies, together with the advances intelligent algorithms, which able perform online pattern recognition classification seamless results, at front line of high-performance coaching. In this work, an data analytics system for swimmer performance is proposed. The includes (i)...

In this paper, we exploit a recently introduced coding algorithm called multidimensional multiscale parser (MMP) as an alternative to the traditional transform quantization-based methods. MMP uses approximate pattern matching with adaptive dictionaries that contain concatenations of scaled versions previously encoded image blocks. We propose use predictive schemes modify source's probability distribution, in order favour efficiency MMP's dictionary adaptation. Statistical conditioning is...

In this paper, we propose a new encoder for scanned compound documents, based upon recently introduced coding paradigm called multidimensional multiscale parser (MMP). MMP uses approximate pattern matching, with adaptive dictionaries that contain concatenations of scaled versions previously encoded image blocks. These features give the ability to adjust input image's characteristics, resulting in high efficiencies wide range types. This versatility makes good candidate digital document...

A complete encoding solution for efficient intra-based depth map compression is proposed in this paper. The algorithm, denominated predictive coding (PDC), was specifically developed to efficiently represent the characteristics of maps, mostly composed by smooth areas delimited sharp edges. At its core, PDC involves a directional intra prediction framework and straightforward residue method, combined with an optimized flexible block partitioning scheme. In order improve algorithm presence...

This work presents a contribution to advance current solutions for the problem of melanoma detection based on deep learning (DL) approaches. is an active research field, which aims aid and classification (the most lethal type skin cancer) with non-invasive solutions. By exploiting both 2D 3D characteristics lesion surface, proposed approach advances beyond commonly used colour features dermoscopic images. Two competing methods are exploited, namely Multiple Instance Learning (MIL) DL,...

This paper presents the results of a multiscale pattern-matching-based ECG encoder, which employs simple preprocessing techniques for adapting input signal. Experiments carried out with records from Massachusetts Institute Technology-Beth Israel Hospital database show that proposed scheme is effective, outperforming some state-of-the-art schemes described in literature.

In this paper we present a new segmentation method for the multidimensional multiscale parser (MMP) algorithm. previous works have shown that, text and compound images, MMP has better compression efficiency than state-of-the-art transform-based encoders like JPEG2000 H.264/AVC; however, it is still inferior to them smooth images. improve performance of images by employing more flexible block scheme one defined in original The partition allows exploit image's structure much adaptive effective...

The Multidimensional Multiscale Parser-based (MMP) image coding algorithm, when combined with flexible partitioning and predictive techniques (MMP-FP), provides state-of-the-art performance. In this paper we investigate the use of adaptive least-squares prediction in MMP. linear coefficients implicitly embed local texture characteristics, are computed based on a block's causal neighborhood (composed already reconstructed data). Thus, intra mode is adaptively adjusted according to context no...

In this paper we present a new method for image coding that is able to achieve good results over wide range of types. This work based on the multidimensional multiscale parser (MMP) algorithm (M. de Carvalho et al., 2002), allied with an intra frame predictive scheme. MMP has been shown have, large class data, including texts, graphics, mixed images and textures, compression efficiency comparable (and, in several cases, well above) one state-of-the-art encoders. However, smooth grayscale...