Abstract: A bitstream that stores encoded image data is described. In addition to the compressed data for color planes of the image, signals identifying respective deblocking filters is identified for the different color planes of the image. The deblocking filters may include those having different lengths for a luma plane as compared to one or more chroma planes of the image. One or more of the color planes, such as the luma plane, may have different filters for filtering reconstructed pixels vertically as compared to filtering the reconstructed pixels horizontally.

Abstract: The present invention a sparse optimization method based on cross-shaped three-dimensional imaging sonar array, comprising the following steps: first, constructing a beam pattern simultaneously applicable to a near field and a far field based on a cross-shaped array; then, constructing an energy function required by sparse optimization according to the beam pattern; then, introducing an array element position disturbance into a simulated annealing algorithm to increase the degree of freedom of the sparse process and increase the sparse rate of the sparse array, and using the simulated annealing algorithm to sparse optimization of the energy function; finally, after optimization, a sparse optimization cross-shaped array is obtained. The present invention ensures that the three-dimensional imaging sonar system has the desired performance at any distance, and greatly reduces the hardware complexity of the system.

Abstract: The present invention discloses a ViBe-based three-dimensional sonar point cloud image segmentation method, characterized by including: (1) acquiring sonar data, and converting three-dimensional sonar depth image data corresponding to each frame of the sonar data to point cloud data under an orthogonal coordinate system; (2) sampling the point cloud data, and down-sampling the point cloud data to a plurality of adjacent voxels with side length being R by taking a variable resolution R as a function; (3) carrying out image segmentation on the down-sampled point cloud data by a ViBe algorithm; (4) carrying out accumulative scoring on each voxel according to an image segmentation result, and sorting foreground data and background data according to accumulative score; and (5) clustering the foreground data, and then carrying out expansion operation on the foreground data by taking an original point in the voxel as a center to obtain final foreground point cloud data.

Abstract: The present invention had disclosed an embedded processor based 3D acoustic imaging real-time signal processing device of modularized design; the system comprises an embedded GPU signal processing subsystem, a signal interaction subsystem and a signal acquisition subsystem. The system takes Tegra K1 embedded GPU processor as the core; Tegra K1 embedded GPU processor is provided with features of OpenGL4.4, OpenGL ES 3.1 and CUDA, which has high parallel image processing capability and abundant high-speed data interconnection interface; it is especially applicable to high-speed data transmission and effective calculation of image algorithm for 3D acoustic imaging real-time signal processing device. Meanwhile, it can realize high-speed data interaction between signal processing subsystem and numerous signal acquisition subsystems; the whole system has powerful data interaction capability and real-time parallel processing capability.

Abstract: The present invention discloses a point cloud mean background subtraction based method for 3D sonar image modeling, comprising: (1) obtaining sonar data, and convert 3D sonar range image information corresponding to sonar data per frame into point cloud data for overall coordinate; such point cloud data will form image pixels; (2) taking the mean value u(x,y,z) of pixels at the same position in a series sequential frame images as pixels at the same position in the background model to obtain the background model; define threshold value TH for background standard based on pixel in each image; (3) testing current frame image I(x,y,z) based on background model and threshold value TH to obtain output image; (4) using current frame image I(x,y,z) to update background model and threshold value TH.

Abstract: The present invention discloses a distance statistics based method for 3D sonar point cloud image enhancement, comprising the following steps: (1) obtaining sonar data, and converting 3D sonar range image information corresponding to sonar data per frame into point cloud data in global coordinate; (2) using a kd-tree to search the point cloud data, and calculate Euclidean distance Lij between point Pi and the nearest K point cloud data; wherein, value range of i and j is 1?i?N and 1?j?K respectively; N refers to the total quantity of point cloud data; (3) excluding point cloud data corresponding to mean value of Lij which do not match the certain Gaussian distribution, and complete enhancement of 3D sonar point cloud image. Such method features in easy operation, high efficiency and convenience, which can effectively remove outlier points to minimize noise, and enhance point cloud image.

Abstract: The present invention discloses a point cloud mean background subtraction based method for 3D sonar image modeling, comprising: (1) obtaining sonar data, and convert 3D sonar range image information corresponding to sonar data per frame into point cloud data for overall coordinate; such point cloud data will form image pixels; (2) taking the mean value u(x, y, z) of pixels at the same position in a series sequential frame images as pixels at the same position in the background model to obtain the background model; define threshold value TH for background standard based on pixel in each image; (3) testing current frame image I(x, y, z) based on background model and threshold value TH to obtain output image; (4) using current frame image I(x, y, z) to update background model and threshold value TH.

Abstract: The present invention a sparse optimization method based on cross-shaped three-dimensional imaging sonar array, comprising the following steps: first, constructing a beam pattern simultaneously applicable to a near field and a far field based on a cross-shaped array; then, constructing an energy function required by sparse optimization according to the beam pattern; then, introducing an array element position disturbance into a simulated annealing algorithm to increase the degree of freedom of the sparse process and increase the sparse rate of the sparse array, and using the simulated annealing algorithm to sparse optimization of the energy function; finally, after optimization, a sparse optimization cross-shaped array is obtained. The present invention ensures that the three-dimensional imaging sonar system has the desired performance at any distance, and greatly reduces the hardware complexity of the system.

Abstract: The present invention discloses a distance statistics based method for 3D sonar point cloud image enhancement, comprising the following steps: (1) obtaining sonar data, and converting 3D sonar range image information corresponding to sonar data per frame into point cloud data in global coordinate; (2) using a kd-tree to search the point cloud data, and calculate Euclidean distance Lij between point Pi and the nearest K point cloud data; wherein, value range of i and j is 1?i?N and 1?j?K respectively; N refers to the total quantity of point cloud data; (3) excluding point cloud data corresponding to mean value of Lij which do not match the certain Gaussian distribution, and complete enhancement of 3D sonar point cloud image. Such method features in easy operation, high efficiency and convenience, which can effectively remove outlier points to minimize noise, and enhance point cloud image.

Abstract: The present invention discloses a ViBe-based three-dimensional sonar point cloud image segmentation method, characterized by including: (1) acquiring sonar data, and converting three-dimensional sonar depth image data corresponding to each frame of the sonar data to point cloud data under an orthogonal coordinate system; (2) sampling the point cloud data, and down-sampling the point cloud data to a plurality of adjacent voxels with side length being R by taking a variable resolution R as a function; (3) carrying out image segmentation on the down-sampled point cloud data by a ViBe algorithm; (4) carrying out accumulative scoring on each voxel according to an image segmentation result, and sorting foreground data and background data according to accumulative score; and (5) clustering the foreground data, and then carrying out expansion operation on the foreground data by taking an original point in the voxel as a center to obtain final foreground point cloud data.

Abstract: The present invention had disclosed an embedded processor based 3D acoustic imaging real-time signal processing device of modularized design; the system comprises an embedded GPU signal processing subsystem, a signal interaction subsystem and a signal acquisition subsystem. The system takes Tegra K1 embedded GPU processor as the core; Tegra K1 embedded GPU processor is provided with features of OpenGL4.4, OpenGL ES 3.1 and CUDA, which has high parallel image processing capability and abundant high-speed data interconnection interface; it is especially applicable to high-speed data transmission and effective calculation of image algorithm for 3D acoustic imaging real-time signal processing device. Meanwhile, it can realize high-speed data interaction between signal processing subsystem and numerous signal acquisition subsystems; the whole system has powerful data interaction capability and real-time parallel processing capability.

Abstract: This invention discloses a real-time phased array 3D acoustic imaging sonar processing system and method. The system comprises a 3D sonar dot data collection module, a 3D sonar dot data uploading module and a real-time 3D sonar dot data processing module of PC terminal; the method includes the following content: make use of two-stage FPGA signal processing to realize real-time formation of electronic focusing wave beam, and acquire 3D sonar dot data; further transmit 3D sonar dot data to PC terminal for setting and acquisition of directives; PC terminal aims to receive 3D sonar dot data for real-time processing: This includes real-time single-frame multilayer reconstruction, image registration and splice, 3D visualization and real-time saving of data. This invention features in compact structure, high real-time precision, clear image, easy alternation and high extendibility, which has effectively realized the real-time 3D processing of sonar targets.

Abstract: This invention discloses a FPGA based high-speed low-latency floating-point accumulation and its implementation method. Floating accumulation of this invention comprises a floating-point adder unit, numerous intermediate result buffers, an input control unit and an output control unit. The floating-point accumulation implementation method of this invention is used for gradation of the whole accumulation calculation process to ensure cross execution of accumulation calculation processes and graded storage of intermediate results of accumulation calculation at different levels; meanwhile, the operation in the mode of pure flow line can significantly improve utilization rate of internal floating-point adder, and maintain relatively low latency to output of final results of floating-point accumulation calculation.

Abstract: The present invention discloses a multi-core processor based high-speed digital textile printing processing system, comprising a gigabit Ethernet interface, a I2C interface, a Stream IO interface and a multi-core processor; the multi-core processor comprises a command receiving unit, a command processing unit, a command output unit, a data receiving unit, a compressed data buffer unit, a data decompression unit, a decompressed data buffer unit and a data output unit; meanwhile, the present invention also disclosed a multi-core processor based high-speed digital textile printing processing method. The present invention is centered on high-performance multi-core processor, which aims to implement high-speed transmission of printing data from PC to printing nozzle via the gigabit Ethernet and Stream IO interface as well as processing and transfer of printing commands via the gigabit Ethernet and I2C interface.

Abstract: The present invention discloses a multi-core processor based image data rotating processing system for high-speed digital textile printers, including a data receiving equipment, a data analysis and processing equipment, a data transmission channel and data output equipment. The present invention also discloses a multi-core processor based image data rotating processing method for high-speed printers; it aims to receive data via the Ethernet interface, use numerous cores of the processor for parallel data processing, and implement data output via FPGA. As compared with prior arts, the system and method of the present invention can significantly improve the data gyration efficiency and output, and implement high yield of digital textile printers.

Abstract: The present invention discloses a multi-core processor based high-speed digital textile printing processing system, comprising a gigabit Ethernet interface, a I2C interface, a Stream IO interface and a multi-core processor; the multi-core processor comprises a command receiving unit, a command processing unit, a command output unit, a data receiving unit, a compressed data buffer unit, a data decompression unit, a decompressed data buffer unit and a data output unit; meanwhile, the present invention also disclosed a multi-core processor based high-speed digital textile printing processing method. The present invention is centered on high-performance multi-core processor, which aims to implement high-speed transmission of printing data from PC to printing nozzle via the gigabit Ethernet and Stream IO interface as well as processing and transfer of printing commands via the gigabit Ethernet and I2C interface.

Abstract: This invention discloses a FPGA based high-speed low-latency floating-point accumulation and its implementation method. Floating accumulation of this invention comprises a floating-point adder unit, numerous intermediate result buffers, an input control unit and an output control unit. The floating-point accumulation implementation method of this invention is used for gradation of the whole accumulation calculation process to ensure cross execution of accumulation calculation processes and graded storage of intermediate results of accumulation calculation at different levels; meanwhile, the operation in the mode of pure flow line can significantly improve utilization rate of internal floating-point adder, and maintain relatively low latency to output of final results of floating-point accumulation calculation.

Abstract: This invention discloses a real-time phased array 3D acoustic imaging sonar processing system and method. The system comprises a 3D sonar dot data collection module, a 3D sonar dot data uploading module and a real-time 3D sonar dot data processing module of PC terminal; the method includes the following content: make use of two-stage FPGA signal processing to realize real-time formation of electronic focusing wave beam, and acquire 3D sonar dot data; further transmit 3D sonar dot data to PC terminal for setting and acquisition of directives; PC terminal aims to receive 3D sonar dot data for real-time processing: This includes real-time single-frame multilayer reconstruction, image registration and splice, 3D visualization and real-time saving of data. This invention features in compact structure, high real-time precision, clear image, easy alternation and high extendibility, which has effectively realized the real-time 3D processing of sonar targets.