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    • 21. 发明授权
    • Method and apparatus for assessing image quality using quantization codes
    • 使用量化代码评估图像质量的方法和装置
    • US08948521B2
    • 2015-02-03
    • US13521943
    • 2011-01-11
    • Dong-O KimRae-Hong Park
    • Dong-O KimRae-Hong Park
    • G06K9/68G06T7/00
    • G06T7/0002G06T2207/30168
    • Provided is a method for assessing image quality using quantization codes, which includes: filtering an original image and a distorted image; generating phase quantization codes from the filtering result; calculating a Hamming difference between the phase quantization code of the original image and the phase quantization code of the distorted image; and assessing image quality of the distorted image by using the calculated Hamming difference. According to the present disclosure, since pixel values of the original image and the distorted image are mapped onto a quantized complex plane and then binary code operation is performed, it is possible to easily implement image quality assessing hardware and also ensure excellent image quality assessing performance.
    • 提供了一种使用量化码来评估图像质量的方法,其包括:对原始图像和失真图像进行滤波; 从滤波结果生成相位量化码; 计算原始图像的相位量化码与失真图像的相位量化码之间的汉明差; 并使用计算的汉明差来评估失真图像的图像质量。 根据本公开,由于原始图像和失真图像的像素值被映射到量化复平面上,因此执行二进制代码操作,可以容易地实现图像质量评估硬件并且还确保优异的图像质量评估性能 。
    • 26. 发明申请
    • Method and apparatus for adaptive false contour reduction
    • 用于自适应假轮廓降低的方法和装置
    • US20060269159A1
    • 2006-11-30
    • US11330055
    • 2006-01-12
    • Jae-Seung KimWonseok AhnRae-Hong ParkBo LimJi Lee
    • Jae-Seung KimWonseok AhnRae-Hong ParkBo LimJi Lee
    • G06K9/42
    • G06T5/002G06T5/20G06T5/50G06T7/12G06T2207/20012G06T2207/20192
    • A method for adaptive false contour reduction includes: detecting contour location information by removing a flat region having certain brightness values from a first input image based on a bright value difference between the first input image and a second input image with a bit depth of the first input image reduced; detecting false-contour direction and location information by measuring directional contrast of the flat region-removed first image, and distinguishing the false contour area and an edge area out of the false contour location information based on the measured contrast; and smoothing the false contour area by using the false contour direction and location information, and removing the false contour from the first input image. Thus, a flat region can be automatically removed by using a brightness value difference between a bit depth-reduced image and an original input image and detect a false contour, thereby enhancing a precision degree of false contour detection. Further, signal components can be prevented from being degraded by performing smoothing over only a false contour.
    • 一种用于自适应假轮廓降低的方法包括:通过基于第一输入图像和第二输入图像之间的亮度值从第一输入图像中去除具有特定亮度值的平坦区域来检测轮廓位置信息,其中第一 输入图像减少; 通过测量平坦区域去除的第一图像的方向对比度来检测假轮廓方向和位置信息,并且基于测量的对比来区分假轮廓位置信息中的假轮廓区域和边缘区域; 以及通过使用所述假轮廓方向和位置信息来平滑所述假轮廓区域,以及从所述第一输入图像中去除所述假轮廓。 因此,可以通过使用位深度缩小图像和原始输入图像之间的亮度值差来自动去除平坦区域,并检测假轮廓,从而提高伪轮廓检测的精确度。 此外,通过仅对假轮廓进行平滑,可以防止信号分量的劣化。