LOW POWER ULTRA-HD VIDEO HARDWARE ENGINE
    181.
    发明申请
    LOW POWER ULTRA-HD VIDEO HARDWARE ENGINE 有权
    低功率超高清视频硬件引擎

    公开(公告)号:US20150271494A1

    公开(公告)日:2015-09-24

    申请号:US14661711

    申请日:2015-03-18

    CPC classification number: H04N19/115 G06F13/28 H04N19/423

    Abstract: A low power video hardware engine is disclosed. The video hardware engine includes a video hardware accelerator unit. A shared memory is coupled to the video hardware accelerator unit, and a scrambler is coupled to the shared memory. A vDMA (video direct memory access) engine is coupled to the scrambler, and an external memory is coupled to the vDMA engine. The scrambler receives an LCU (largest coding unit) from the vDMA engine. The LCU comprises N×N pixels, and the scrambler scrambles N×N pixels in the LCU to generate a plurality of blocks with M×M pixels. N and M are integers and M is less than N.

    Abstract translation: 公开了一种低功率视频硬件引擎。 视频硬件引擎包括视频硬件加速器单元。 共享存储器耦合到视频硬件加速器单元,并且加扰器耦合到共享存储器。 vDMA(视频直接存储器访问)引擎耦合到加扰器,并且外部存储器耦合到vDMA引擎。 加扰器从vDMA引擎接收LCU(最大编码单元)。 LCU包括N×N个像素,扰频器对LCU中的N×N个像素进行加扰,以产生具有M×M个像素的多个块。 N和M是整数,M小于N.

    METHODS AND APPARATUS TO GENERATE WIDE DYNAMIC RANGE IMAGES
    182.
    发明申请
    METHODS AND APPARATUS TO GENERATE WIDE DYNAMIC RANGE IMAGES 有权
    生成宽动态范围图像的方法和装置

    公开(公告)号:US20150207974A1

    公开(公告)日:2015-07-23

    申请号:US14599201

    申请日:2015-01-16

    CPC classification number: H04N5/2355 H04N5/345 H04N5/35581

    Abstract: Methods and apparatus to generate wide dynamic range images are disclosed. An example apparatus includes a first processing block having first input, second input to receive input data from an image sensor, and first output; a second processing block having third input, fourth input to receive input data from the image sensor, and second output, at least one of the first and second outputs to output a WDR image based on at least two of the first, second, third and fourth inputs; an architecture recognizer having fifth input and third output, the third output to convey an architecture type of the image sensor; a function selector having fourth output to identify at least one of the first and second processing blocks based on the third output; and a sensor adapter having seventh input coupled to the fourth output and having fifth output coupled to the first and third inputs.

    Abstract translation: 公开了产生宽动态范围图像的方法和装置。 示例性装置包括具有第一输入的第一处理块,用于从图像传感器接收输入数据的第二输入和第一输出; 具有第三输入的第二处理块,用于接收来自图像传感器的输入数据的第四输入,以及第二输出,第一和第二输出中的至少一个输出,基于第一,第二,第三和第三输入中的至少两个,输出WDR图像; 第四输入; 具有第五输入和第三输出的架构识别器,用于传送图像传感器的架构类型的第三输出; 功能选择器,具有第四输出,用于基于第三输出来识别第一和第二处理块中的至少一个; 以及传感器适配器,其具有耦合到第四输出的第七输入端,并具有耦合到第一和第三输入端的第五输出端。

    METHOD AND APPARATUS FOR DECODING A PROGRESSIVE JPEG IMAGE
    183.
    发明申请
    METHOD AND APPARATUS FOR DECODING A PROGRESSIVE JPEG IMAGE 有权
    用于解码进步JPEG图像的方法和装置

    公开(公告)号:US20150023609A1

    公开(公告)日:2015-01-22

    申请号:US14335099

    申请日:2014-07-18

    Abstract: A progressive JPEG (joint photographic experts group) decoder is disclosed. The progressive JPEG decoder includes a processing unit that receives a plurality of progressive scans and generates a plurality of modified progressive scans (MPSs). A baseline JPEG decoder, coupled to the processing unit, includes a Huffman decoder, an inverse quantization unit and an inverse transform unit. The Huffman decoder receives a current MPS and generates a set of transform coefficients corresponding to the current MPS. The processing unit adds a set of transform coefficients corresponding to a previous MPS to the set of transform coefficients corresponding to the current MPS, and the processing unit generates quantization indices. The inverse quantization unit estimates inverse quantization values based on the quantization indices. The inverse transform unit estimates inverse transform decoded values based on the estimated inverse quantization values and generates a set of pixels corresponding to the current MPS.

    Abstract translation: 公开了一种渐进的JPEG(联合摄影专家组)解码器。 逐行JPEG解码器包括接收多个渐进扫描并产生多个修改的逐行扫描(MPS)的处理单元。 耦合到处理单元的基线JPEG解码器包括霍夫曼解码器,逆量化单元和逆变换单元。 霍夫曼解码器接收当前的MPS并产生与当前MPS对应的一组变换系数。 处理单元将与先前MPS对应的一组变换系数与对应于当前MPS的变换系数组相加,并且处理单元生成量化索引。 逆量化单元基于量化索引来估计反量化值。 逆变换单元基于估计的反量化值估计逆变换解码值,并生成与当前MPS对应的一组像素。

    Delayed Duplicate I-Picture for Video Coding
    184.
    发明申请
    Delayed Duplicate I-Picture for Video Coding 有权
    延迟重复的I-Picture用于视频编码

    公开(公告)号:US20130114715A1

    公开(公告)日:2013-05-09

    申请号:US13671344

    申请日:2012-11-07

    CPC classification number: H04N19/895 H04N19/107 H04N19/172 H04N19/39 H04N19/65

    Abstract: A method is provided that includes receiving pictures of a video sequence in a video encoder, and encoding the pictures to generate a compressed video bit stream that is transmitted to a video decoder in real-time, wherein encoding the pictures includes selecting a picture to be encoded as a delayed duplicate intra-predicted picture (DDI), wherein the picture would otherwise be encoded as an inter-predicted picture (P-picture), encoding the picture as an intra-predicted picture (I-picture) to generate the DDI, wherein the I-picture is reconstructed and stored for use as a reference picture for a decoder refresh picture, transmitting the DDI to the video decoder in non-real time, selecting a subsequent picture to be encoded as the decoder refresh picture, and encoding the subsequent picture in the compressed bit stream as the decoder refresh picture, wherein the subsequent P-picture is encoded as a P-picture predicted using the reference picture.

    Abstract translation: 提供了一种方法,其包括接收视频编码器中的视频序列的图像,并对图像进行编码以生成被实时发送到视频解码器的压缩视频比特流,其中编码图像包括选择图像为 编码为延迟重复帧内预测图像(DDI),其中图像将被编码为帧间预测图像(P图像),将图像编码为帧内预测图像(I图像)以生成DDI 其中,I图像被重建和存储以用作解码器刷新图像的参考图像,以非实时的方式将DDI发送到视频解码器,选择待编码的后续图像作为解码器刷新图像,以及编码 压缩比特流中的后续图像作为解码器刷新图像,其中后续P图像被编码为使用参考图片预测的P图像。

    Software sharing across multiple cores

    公开(公告)号:US12242379B2

    公开(公告)日:2025-03-04

    申请号:US18082693

    申请日:2022-12-16

    Abstract: In an example, a method includes storing code for a first central processing unit (CPU) executing a first application in a first region of a memory, and storing code for a second CPU executing a second application in a second region of the memory. The method includes storing shared code for the first CPU and the second CPU in a third region of the memory. The method includes storing read-write data for the first CPU in a fourth region of the memory and storing read-write data for the second CPU in a fifth region of the memory. The method includes translating a first address from a first unique address space for the first CPU to a shared address space in the third region, and translating a second address from a second unique address space for the second CPU to the shared address space in the third region.

    Suppression of clipping artifacts from color conversion

    公开(公告)号:US12131504B2

    公开(公告)日:2024-10-29

    申请号:US17538268

    申请日:2021-11-30

    CPC classification number: G06T7/90 G06T1/20 G06T2207/10024 G06T2207/20208

    Abstract: Techniques for image processing including receiving input image data, wherein the input image data includes data associated with a clear color channel, receiving a color offset value associated with a color channel, wherein color values for the color channel are not provided in the input image data, based on the color offset value, generating intermediate estimated color values for the color channel, wherein generating the intermediate estimated color values includes: clipping color values that have a magnitude greater than the color offset value, and adjusting color values that have a magnitude less than the color offset value based on the color offset value, applying a color correction function to the intermediate estimated color values based on the color offset value to determine color corrected estimated color values, and outputting the color corrected estimated color values.

    Packet storage based on packet properties

    公开(公告)号:US12126549B2

    公开(公告)日:2024-10-22

    申请号:US18357710

    申请日:2023-07-24

    CPC classification number: H04L49/9042 H04L49/109 H04L67/568 H04L69/22

    Abstract: In an example, a system includes a network port that receives a packet; a first memory; a second memory; and a packet analyzer coupled to the network port. The packet analyzer operates to divide the packet into multiple fragments, analyze each of the multiple fragments to determine whether the corresponding fragment has a first priority level or a second, lower, priority level, determine whether to store each of the multiple fragments in the first memory or the second memory based on the priority level determined for that fragment, store each fragment determined to have the first priority level in the first memory, and store each fragment determined to have the second priority level in the second memory. The network port, packet analyzer and the first memory, which may be a cache memory, may be embodied on a chip, and the second memory may be external to the chip.

    Scheduling of External Block Based Data Processing Tasks on a Hardware Thread Scheduler

    公开(公告)号:US20240345870A1

    公开(公告)日:2024-10-17

    申请号:US18748423

    申请日:2024-06-20

    CPC classification number: G06F9/4812 G06F9/5027 G06F2209/5018

    Abstract: Systems and method are provided for flexibly configuring task schedulers and respectively associated data processing nodes to execute threads of tasks using a hardware thread scheduler (HTS). The data processing nodes may be hardware accelerators, channels of a direct memory access circuit and external nodes such as a processor executing software instructions. Each hardware accelerator is coupled to a respective hardware task scheduler, each channel is coupled to a respective channel task scheduler, and each external node is coupled to a proxy task scheduler. The task schedulers communicate via pending and decrement signals with a hardware scheduler crossbar. With this arrangement, the HTS couples a first subset of task schedulers in a first data processing order with the associated data processing nodes performing the tasks, and couples a second subset of task schedulers in a second data processing order with the associated data processing nodes performing the tasks.

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