An extension to the motion-constrained tile sets SEI message provides functionality to signal all tiles are independently decodable and to signal the ROIs that may have more than one tile per ROI. With this extension, the functionality to redefine any independently decodable region-of-interest in a CVS at a coding tree unit level based on user interactivity is enabled. The extension supports the interactivity utilized in various applications such as interactive Ultra High Definition Television (UHDTV), dynamic high-quality zoom-in application, interactive on-demand, e-learning, smart surveillance and many other applications. Additionally, the temporal MCTS SEI message is able to be used by an encoder for tiled streaming to signal explicitly to the decoder that the decoder need only to display the ROI.

Extensions of motion-constrained tile sets sei message for interactivity

Described is an apparatus and method for data compression using compressive sensing in a wearable device. Described is also a machine-readable storage media having instruction stored thereon, that when executed, cause one or more processors to perform an operation comprising: receive an input signal from a sensor; convert the input signal to a digital stream; and symmetrically pad on either ends of the digital stream with a portion of the digital stream to form a padded digital stream.

Apparatus and method for data compression in a wearable device

An image compression method based on an FPGA (Field Programmable Gate Array) is carried out on the FPGA and comprises the following steps: calculating the number m of layers of wavelet transform according to the size of an image, and carrying out m layers of wavelet transform on the image; Obtaining a scanning sequence list of all pixel points in the image according to the layer number m of wavelet transform; Obtaining the number of coding layers for coding the image pixel points according to the maximum value of the absolute values of the values of all the pixel points in the image after wavelet transformation, and obtaining a coded pixel coefficient importance list and a pixel subset importance list according to the number of coding layers; And according to the scanning sequence list, the pixel coefficient importance list and the pixel subset importance list, carrying out classification coding on pixel points of the image, carrying out fault-tolerant control coding, and splicing a classification coding result and the fault-tolerant control coding to compress the image. According to the method, the problem that traditional dynamic link table coding is not easy to realize in the FPGA is solved, the advantages of SPIHT image compression are continued, and the fault tolerance during image compression is improved.

Image compression method based on FPGA

Systems, devices, and methods for encoding a plurality of images by an encoder where the encoder determines a set of subbands associated with an input image, determines a set of wavelet coefficients associated with each subband, generates a wavelet tree comprising a set of nodes and a maximum quantization level for a set of descendants of the set of nodes of the wavelet tree. Then, determines if the maximum quantization level is less than a threshold and sets the wavelet coefficient to zero if it is not, otherwise encodes the maximum quantization level, and encodes the set of wavelet coefficients for transmission in a bit stream comprising the encoded maximum quantization level and the encoded set of wavelet coefficients.

Low complexity and memory efficient image CODEC

Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are noninvasive neuroimaging technologies providing functional mapping of stimulus activated voxels and detailed connectivity structures in the brain, which are traditionally based on simplified linear models. Despite the unique functional and structural representations achievable by fMRI and DTI, respectively, both representations still need validations of the assumptions embedded in the analysis of the data. Recent research efforts emphasize either a data driven or a hybrid approach to fMRI data analysis for more robust characterization of the data. Here we propose a methodology for finding relatively quantitative axonal connectivity pathways among distinct functional regions in the brain using appropriate image analysis techniques with the ultimate goal of generating a multidimensional structure-function correlation map. To achieve this goal, in our preliminary studies we have used independent component analysis (ICA) on fMRI data to locate the terminal seed points on axonal pathways segmented from fractional anisotropic (FA) DTI slices. The co-registered fMRI, and FA-DTI data with the corresponding anatomical image were color coded for visualization. A robust segmentation of axonal pathways was obtained by using a nonparametric estimation of Gaussian mixture model based on the transformation and analysis of the D(R) (distortion-rate) curve.

Generating structure-function correlations by ICA- based mapping of activation patterns on co-registered fMRI and FA-DTI data

Despite the approval of a new standard in 2009, JPEG-extended range lossless, current digital products still employ previous standards for lossless image compression, such as JPEG, JPEG2000, JPEG-LS, etc. Wavelet-based codecs can provide abundant functionalities and excellent compression efficiency. Among them, the backward coding of wavelet trees (BCWT) algorithm offers lower complexity and consumes less internal buffer memory without sacrificing quality at similar compression ratios (CR) when compared to other wavelet-based codecs, such as JPEG2000 and set partitioning in hierarchical trees (SPIHT). A line-based BCWT was developed for further reduction of internal buffer memory. A very efficient line-based lossless BCWT compression algorithm is presented. Lossless color and lossless wavelet transform are employed and the original BCWT algorithm is modified for lossless operation, including incorporation of adaptive arithmetic coding. In order to eliminate coding redundancies, a set to zeros method and a zero tree detection algorithm are proposed, which significantly enhance the boundary condition CR performance while reserving the algorithm’s advantages. Tests and analysis results show that the lossless BCWT algorithm requires less memory and computational resources than SPIHT and JPEG2000, while retaining image quality comparable to the standard image codecs, therefore, lossless BCWT is quite suitable for implementation in modern digital technologies.

Efficient lossless codec for still color images with backward coding of wavelet trees

A robust stereoscopic method is presented for rapid identification of hidden 3D objects by extracting edge and other features from computed depth planes using only a small number of X-ray projections acquired with a low-cost portable X-ray imager. The portable X-ray imager acquires X-ray projections with a single fixed sensor from different viewing angles by rotating an X-ray source attached to the end of a pivot arm. Knowing the geometry of the X-ray imaging system, a series of depth planes are computed to extract the significant features of the hidden objects for quick identification. The proposed hidden object identification algorithm can be easily parallelised and embedded in portable devices for real-time applications.

Rapid identification of 3D object features using limited number of X-ray projections

Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various
perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor
tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may
produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed
probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data
and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a
complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may
reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG)
source localization patterns.

Bian Li

Papers

Low complexity and memory efficient image CODEC

Generating structure-function correlations by ICA- based mapping of activation patterns on co-registered fMRI and FA-DTI data

Efficient lossless codec for still color images with backward coding of wavelet trees

Rapid identification of 3D object features using limited number of X-ray projections

fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization