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    Super-resolution convolutional neural network with gradient image detection
    2.
    发明授权
    Super-resolution convolutional neural network with gradient image detection 有权

    公开(公告)号：US11366624B2

    公开(公告)日：2022-06-21

    申请号：US16834772

    申请日：2020-03-30

    Applicant: KYOCERA DOCUMENT SOLUTIONS INC.

    Inventor： Sheng Li ,  Dongpei Su

    IPC: G06F3/12 ,  G06K9/62 ,  G06T3/40 ,  G06N3/04

    Abstract: An example system includes a processor and a non-transitory computer-readable medium having stored therein instructions that are executable to cause the system to perform various functions. The functions include obtaining an image associated with a print job, and providing the image as input to a convolutional neural network. The convolutional neural network includes a residual network, upscaling layers, and classification layers configured to detect whether the image is an artificial image having a computer-generated image gradient. The functions also include determining, based on an output of the classification layers, that the image is an artificial image having a computer-generated image gradient. Further, the functions include, based on determining that the image is an artificial image having a computer-generated image gradient, providing the image to an upscaling module of a print pipeline for upscaling rather than using an output of the upscaling layers for the upscaling.

    Apparatus and method for data decoding
    3.
    发明授权
    Apparatus and method for data decoding 有权
    数据解码装置及方法

    公开(公告)号：US09538044B2

    公开(公告)日：2017-01-03

    申请号：US14664335

    申请日：2015-03-20

    Applicant: KYOCERA Document Solutions Inc.

    Inventor： Dongpei Su ,  Kenneth A. Schmidt ,  Thien-Phuc Nguyen Do ,  Sheng Li

    IPC: H03M7/40 ,  H04N1/411 ,  H04N19/129 ,  H04N19/124 ,  H04N19/176 ,  H04N19/91

    CPC classification number: H04N1/4115 ,  H04N19/124 ,  H04N19/129 ,  H04N19/176 ,  H04N19/91 ,  H04N2201/0094

    Abstract: A computer-implemented method comprises receiving a data stream that includes a series of code words that encodes a respective series of pixel data according to a first entropy coding lookup table, and processing the data stream to determine if there is a match between a first code word and a consecutive second code word, and a code word entry in a second entropy coding lookup table. The method also includes, if there is a match, decoding the first code word and the second code word using the second entropy coding lookup table. Further, the method includes, if there is not a match, decoding the first code word using the first entropy coding lookup table.

    Abstract translation: 计算机实现的方法包括：接收包括根据第一熵编码查找表对各个像素数据序列进行编码的一系列码字的数据流，并处理数据流以确定第一代码 字和连续的第二码字，以及第二熵编码查找表中的码字条目。 该方法还包括如果存在匹配，则使用第二熵编码查找表对第一码字和第二码字进行解码。 此外，该方法包括如果不匹配，则使用第一熵编码查找表对第一码字进行解码。

    White Background Protection in SRGAN Based Super Resolution
    4.
    发明申请
    White Background Protection in SRGAN Based Super Resolution 有权

    公开(公告)号：US20220237742A1

    公开(公告)日：2022-07-28

    申请号：US17157990

    申请日：2021-01-25

    Applicant: KYOCERA Document Solutions Inc.

    Inventor： Sheng Li ,  Dongpei Su

    IPC: G06T3/40 ,  G06T5/50

    Abstract: Systems and methods for processing images receive an input image. The systems and methods provide the input image to a first module to increase a resolution of the input image to produce an upscaled image. The systems and methods detect white pixels in the input image. The systems and methods generate a mask associated with the input image. The mask includes mask bits that are set to mark the white pixels in the input image. The systems and methods upscale the mask to produce an upscaled mask matching a resolution of the upscaled image. The systems and methods identify target pixels of the upscaled image that correspond to the set mask bits in the upscaled mask. The systems and methods modify the upscaled image to produce an output image by replacing target pixels of the upscaled image with a replacement pixel having greater whiteness. The systems and methods output the output image.

    Super Resolution Neural Network with Multiple Outputs with Different Upscaling Factors
    5.
    发明申请
    Super Resolution Neural Network with Multiple Outputs with Different Upscaling Factors 有权

    公开(公告)号：US20220237739A1

    公开(公告)日：2022-07-28

    申请号：US17158553

    申请日：2021-01-26

    Applicant: KYOCERA Document Solutions Inc.

    Inventor： Sheng Li ,  Dongpei Su

    IPC: G06T3/40 ,  G06T1/20

    Abstract: Systems and methods upscale an input image by a final upscaling factor. The systems and methods employ a first module implementing a super resolution neural network with feature extraction layers and multiple sets of upscaling layers sharing the feature extraction layers. The multiple sets of upscaling layers upscale the input image according to different respective upscaling factors to produce respective first module outputs. The systems and methods select the first module output with the respective upscaling factor closest to the final upscaling factor. If the respective upscaling factor for the selected first module output is equal to the final upscaling factor, the systems and methods output the selected first module output. Otherwise, the systems and methods provide the selected first module output to a second module that upscales the selected first module output to produce a second module output corresponding to the input image upscaled by the final upscaling factor.

    Digital Image Color Plane Compression
    10.
    发明申请
    Digital Image Color Plane Compression 有权
    数字图像彩色平面压缩

    公开(公告)号：US20170064153A1

    公开(公告)日：2017-03-02

    申请号：US15353556

    申请日：2016-11-16

    Applicant: KYOCERA Document Solutions Inc.

    Inventor： Michael M. Chang ,  Kenneth A. Schmidt ,  Dongpei Su ,  Sheng Li ,  Kendrick Wong ,  Alfred Abkarian ,  Stephen L. Schafer

    IPC: H04N1/64

    CPC classification number: H04N1/648 ,  H04N1/413 ,  H04N1/64 ,  H04N9/64 ,  H04N19/119 ,  H04N2201/0094

    Abstract: An example embodiment may involve obtaining an a×b pixel macro-cell from an input image. The a×b pixel macro-cell may contain 4 non-overlapping m×n pixel cells. The a×b pixels in the a×b pixel macro-cell may have respective color values and may be associated with respective object type tags. The example embodiment may also include selecting a compression technique to either (i) compress the a×b pixel macro-cell as a whole, or (ii) compress the a×b pixel macro-cell by compressing each of the 4 non-overlapping m×n pixel cells separately. The example embodiment may further include compressing the a×b pixel macro-cell according to the selected compression technique, and writing a representation of the compressed a×b pixel macro-cell to a computer-readable output medium.

    Abstract translation: 示例性实施例可以涉及从输入图像获得a×b像素宏小区。 a×b像素宏单元可以包含4个非重叠的m×n个像素单元。 a×b像素宏单元中的a×b像素可以具有各自的颜色值，并且可以与相应的对象类型标签相关联。 该示例性实施例还可以包括选择压缩技术以（i）整体地压缩a×b个像素宏小区，或者（ii）通过压缩4个不重叠的每个像素宏小区来压缩a×b像素宏小区 m×n个像素单元。 示例性实施例还可以包括根据所选择的压缩技术来压缩a×b像素宏小区，并将压缩的a×b像素宏小区的表示写入计算机可读输出介质。

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