CN101682768B - 用于空间隔离的伪影剖析、分类和测量的***和方法 - Google Patents
用于空间隔离的伪影剖析、分类和测量的***和方法 Download PDFInfo
- Publication number
- CN101682768B CN101682768B CN2008800192945A CN200880019294A CN101682768B CN 101682768 B CN101682768 B CN 101682768B CN 2008800192945 A CN2008800192945 A CN 2008800192945A CN 200880019294 A CN200880019294 A CN 200880019294A CN 101682768 B CN101682768 B CN 101682768B
- Authority
- CN
- China
- Prior art keywords
- gradient
- measurement
- graded
- amplitude
- test video
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/004—Diagnosis, testing or measuring for television systems or their details for digital television systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/136—Incoming video signal characteristics or properties
- H04N19/14—Coding unit complexity, e.g. amount of activity or edge presence estimation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
- H04N19/61—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/80—Details of filtering operations specially adapted for video compression, e.g. for pixel interpolation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
- H04N19/86—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression involving reduction of coding artifacts, e.g. of blockiness
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- General Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
Abstract
本发明的实施例涉及一种测量测试视频帧的方法。提供测试视频输入以及伪影测量控制,基于该测试视频输入来执行梯度变化测量并提供梯度变化测量图。
Description
相关申请的交叉引用
本申请要求2007年4月9日提交的题为Systems and Methods forSpatially Isolated Artifact Dissection,Classification and Measurement的美国临时申请No.60/910,819的优先权,该申请通过引用结合到本文中。
技术领域
本发明的实施例涉及视频测试和测量,更特别地涉及视频图像质量(PQ)测量。
背景技术
对于图像质量分析,长期以来已经公认伪影的分类很重要,并且伪影的分类已被结合到诸如ITU-T J.144之类的用于图像质量测量方法的当前国际标准中。本文提出的方法允许分析被检测作为总损伤测量的成分的每一类伪影的比例,不管是如在PSNR中的客观的分析还是如在预测DMOS中的主观的分析。这种按类的损伤剖析对于视频处理分量的诊断分析是有价值的,不管是视频压缩编码器或解码器中的分量,还是视频广播链中的分量。
诸如MPEG-2和H.264之类的视频压缩方法处理视频使用有损耗压缩方法,该方法引入理想地、肉眼看不见的误差。由压缩方法中的损耗引起的任何可见误差自身展现为可能影响也可能不影响视频的感知质量的损伤伪影。存在不同类型的损伤,每种类型具有不同水平的令人反感性。因此,伪影的识别以及按照其的令人反感性对伪影的幅值(magnitude)进行加权已经是预测主观视频质量评价的普遍方法,参见ITU-T J.144。
从视频压缩看到的伪影的示例是以其他方式的平滑梯度、沿弯曲边缘的阶梯式噪声、“蚊式噪声”或边缘周围的响声(ringing)、和/或“繁忙”区域中的方格图案(有时称为绗缝(quilting)或块状结构(blockiness))和模糊来勾画轮廓。除这些压缩伪影之外,还可能发生噪声或较少图像相关的伪影,看起来更像单独像素的误差,如在来自弱模拟接收的“雪花”或“斑点”图像中那样。
已经提出了各种方法以减少图像压缩的影响。伪影减少算法常常可能引入它们自己的伪影,具有一种检查伪影的相对比例的方法对于视频处理HW和SW开发者是有用的。
现有技术已经需要用于每个伪影的识别的主要单独处理,以及在计算时间及成本方面的计算上昂贵的方法以提供必需水平的计算能力,其通常还不保证所检测的伪影种类之间的最佳正交(或分离)以及准确的相对测量。另外,从经分类的伪影的总和不一定包括参考和测试视频之间的所有差异的意义上来说,现有技术缺乏“完整性”。
发明内容
因此,提供了本发明的实施例。一种测量测试视频帧的方法包括基于测试视频输入和伪影测量控制来执行梯度变化测量。在某些实施例中,还连同测试视频输入一起使用参考视频输入。本发明的实施例提供梯度变化测量图。另外,某些实施例提供总结测量(summarymeasurement),或者在每个帧的层级,或者是用于一部分测试视频输入直至整个视频序列的总体总结值。在某些实施例中,可以将梯度变化测量图提供为适合于后续视频处理或测量的掩模(mask)。
在本发明的实施例中,通过基于测试视频对每个像素确定梯度幅度、确定梯度幅值以及梯度方向来进行梯度变化测量。
附图说明
图1是参考视频序列的无损伤视频帧的示例。
图2是测试视频序列的损伤视频帧的示例。
图3是举例说明本发明的实施例的方框图。
图4是对应于图1和图2的描绘边缘成块的旋转的边缘图的示例。
图5是图4的旋转的边缘图的补充(compliment)的示例。
具体实施方式
在图3中以方框图形式示出了本发明的实施例。此装置处理测试下的输入视频,诸如图2的(有点极端)的方块损伤图像。如果可用,还输入相应的参考,例如图1中所示。
在某些实施例中,可以直接输出测量。图4提供了描绘“边缘成块”的旋转的边缘图的示例,其对应于图1和图2中所示的视频帧。图5提供对图4中所示的旋转边缘图的补充的示例。在替换实施例中,使用该测量作为另一次测量的掩模,诸如在Kevin M.Ferguson的题为Picture Quality Diagnostics for Revealing Cause of Perceptibility的美国专利No.7,102,667(‘667专利)中所述,该专利通过引用结合到本文中。
每次测量具有补充,从而使得该测量及其补充相加等于总和。例如,当按照‘667专利用作掩模时该总和是1,或者该总和是测量的最大范围(通常在0~100%的范围内,但可以选择其它单位)。此补充的使用有助于保证完整性。
显式伪影分类和测量包括根据梯度变化分类的那些。再次根据‘667专利,可以将这些显式测量与用于客观和主观测量的权值相加。因此,对所有显式测量的总和的补充是未被显式测量涵盖的任何伪影的隐式测量。再次地,这提供经分类的伪影的集合的完整性,尽管其并不必须彻底地剖析/描绘伪影:通过到目前为止所描绘的显式和隐式类别的进一步处理,可以进行进一步的剖析/描绘。
在3个变化类别内测量梯度(和边缘)变化:1)添加细节:响声(ringing)、蚊式噪声、其它噪声2)去除细节:模糊、降低对比度、一般细节损失3)边缘旋转:方块伪影,“锯齿状图形”等。对于测试和参考视频帧两者,该方法沿四个方向估计梯度以及具有这些取向的它们的相对覆盖边缘:--,|,/&\亦即,对于水平为h,对于垂直为v,对于向前倾斜为f而对于向后倾斜为b
参照图3中所示的实施例,提供了测试视频帧310以及参考视频帧320。在一个替换实施例中,使用测试视频帧和参考视频帧来进行标称(nominal)测量330。标称测量可以向梯度变化测量340提供图或其它数据。在其它实施例中,直接将测试视频帧310连同参考视频帧320一起提供给梯度变化测量340。可以通过提供梯度权值和补充控制的伪影测量控制350来控制梯度变化测量。所述梯度变化测量340提供测量图和总结(summary)360。在某些实施例中,可以使用梯度测量图和总结来提供伪影测量结果370。可替换地,例如使用‘667专利中所描述的处理,将梯度测量图提供为用于进一步处理和测量的掩模380。
在梯度变化测量340内,对每个像素执行以下步骤:1)确定4个基本梯度取向滤波器(filter)中的每一个的梯度幅度3442)确定梯度幅值346。梯度幅值对应于幅度的绝对值。确定4个输出幅值中的最大幅值;以及3)确定对应于最大幅值的梯度方向348。该梯度方向对应于在步骤1中使用的滤波器和相应幅度的符号
如下枚举了方向:0=没有检测到方向(无梯度)1=+h(--:向右,0度)2=+f(/:向右和向上,45度)3=+v(|:向上,90度)4=+b(\:向左和向上,135度)5=-h(--:向左,180度)6=-f(/:向左和向下,-135度)7=-v(|:向下,-90度)8=-b(\:向右和向下,-45度)
测量以下3个类别的梯度变化:1)添加细节:if delta=testGradMag-refGradMag>0,delta2)去除细节:if delta=testGradMag-refGradMag<0,|delta|3)边缘旋转:if(refGradType!=testGradType)&&(testGradType==odd),blocking=testGradMag
由4个取向和极性(1或-1)来表示8个梯度取向。表示4个取向的3×3滤波核的示例是:{-GRAD_SCALE,-GRAD_SCALE,-GRAD_SCALE,//Horizontal(--)Edge0,0,0,GRAD_SCALE,GRAD_SCALE,GRAD_SCALE},{-GRAD_SCALE,-GRAD_SCALE,0,//″Forward″Diagonal(/)Edge-GRAD_SCALE,0,GRAD_SCALE,0,GRAD_SCALE,GRAD_SCALE},{-GRAD_SCALE,0,GRAD_SCALE,//Vertical(|)Edge-GRAD_SCALE,0,GRAD_SCALE,-GRAD_SCALE,0,GRAD_SCALE},{0,GRAD_SCALE,GRAD_SCALE,//″Backward″Diagonal(\)Edge-GRAD_SCALE,0,GRAD_SCALE,-GRAD_SCALE,-GRAD_SCALE,0}其中,在本示例中,GRAD_SCALE=归一化因数=1/(非零元素的数目)=1/6。
然后可以将结果图进行组合以根据例如‘667专利来为每个帧和整个视频序列创建总结测量。
Claims (11)
1.一种测量测试视频帧的方法,包括:
提供测试视频输入;
通过基于所述测试视频输入对每个像素确定4个基本梯度取向滤波器中的每一个的梯度幅度、确定对应于所述梯度幅度的绝对值的梯度幅值以及确定对应于4个梯度幅值中的最大梯度幅值的梯度方向来执行梯度变化的测量;
通过提供梯度权值和补充控制的伪影测量控制来控制所述梯度变化的测量;以及
提供梯度变化的测量图。
2.权利要求1的方法,还包括连同所述测试视频输入一起提供参考视频输入并使用所述测试视频输入和所述参考视频输入两者来执行所述梯度变化的测量。
3.权利要求1的方法,还包括基于所述测试视频输入来执行标称测量,并基于标称测量图来执行所述梯度变化的测量。
4.权利要求3的方法,还包括使用参考视频输入以进行所述标称测量。
5.权利要求1的方法,还包括提供所述梯度变化的测量图作为掩模以进行进一步的视频测量。
6.权利要求1的方法,还包括提供总结梯度变化的测量。
7.权利要求1的方法,还包括提供伪影测量结果。
8.权利要求1的方法,其中,根据所述测试视频输入对帧的每个像素执行所述确定梯度幅度、梯度幅值和梯度方向的步骤。
9.权利要求1的方法,其中,确定梯度幅值包括确定梯度幅度的绝对值。
10.权利要求8的方法,其中,使用四个梯度滤波器的幅度的最大绝对值来确定所述梯度幅值。
11.权利要求10的方法,其中,所述梯度方向对应于在确定梯度幅值的步骤中使用的滤波器和相应梯度幅度的符号。
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US91081907P | 2007-04-09 | 2007-04-09 | |
US60/910,819 | 2007-04-09 | ||
PCT/US2008/059690 WO2008124743A1 (en) | 2007-04-09 | 2008-04-08 | Systems and methods for spatially isolated artifact dissection, classification and measurement |
US12/099,763 US8294770B2 (en) | 2007-04-09 | 2008-04-08 | Systems and methods for spatially isolated artifact dissection, classification and measurement |
US12/099,763 | 2008-04-08 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN101682768A CN101682768A (zh) | 2010-03-24 |
CN101682768B true CN101682768B (zh) | 2013-07-10 |
Family
ID=39637627
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN2008800192945A Expired - Fee Related CN101682768B (zh) | 2007-04-09 | 2008-04-08 | 用于空间隔离的伪影剖析、分类和测量的***和方法 |
Country Status (5)
Country | Link |
---|---|
US (1) | US8294770B2 (zh) |
EP (1) | EP2137976B1 (zh) |
JP (1) | JP5269877B2 (zh) |
CN (1) | CN101682768B (zh) |
WO (1) | WO2008124743A1 (zh) |
Families Citing this family (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7724827B2 (en) | 2003-09-07 | 2010-05-25 | Microsoft Corporation | Multi-layer run level encoding and decoding |
US8374436B2 (en) * | 2008-06-30 | 2013-02-12 | Thomson Licensing | Method for detecting layout areas in a video image and method for generating an image of reduced size using the detection method |
US8184163B2 (en) * | 2009-03-05 | 2012-05-22 | Tektronix, Inc. | Methods and systems for detecting and locating skipped frames in a video sequence |
CN102402787B (zh) * | 2010-09-19 | 2014-01-22 | 上海西门子医疗器械有限公司 | 一种检测图像中条状伪影的***和方法 |
CN102413357A (zh) * | 2010-09-24 | 2012-04-11 | 富泰华工业(深圳)有限公司 | 测试装置及其测试方法 |
US8787443B2 (en) | 2010-10-05 | 2014-07-22 | Microsoft Corporation | Content adaptive deblocking during video encoding and decoding |
US9042458B2 (en) | 2011-04-01 | 2015-05-26 | Microsoft Technology Licensing, Llc | Multi-threaded implementations of deblock filtering |
US9141851B2 (en) * | 2013-06-28 | 2015-09-22 | Qualcomm Incorporated | Deformable expression detector |
US9749686B2 (en) | 2015-09-21 | 2017-08-29 | Sling Media Pvt Ltd. | Video analyzer |
US9693063B2 (en) * | 2015-09-21 | 2017-06-27 | Sling Media Pvt Ltd. | Video analyzer |
EP3714597B1 (en) * | 2018-04-03 | 2023-10-25 | Samsung Electronics Co., Ltd. | Methods and apparatus for determining rotation angle for spherical multimedia content |
Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5920356A (en) * | 1995-06-06 | 1999-07-06 | Compressions Labs, Inc. | Coding parameter adaptive transform artifact reduction process |
EP0961229A2 (en) * | 1998-05-29 | 1999-12-01 | STMicroelectronics, Inc. | Non-linear adaptive image filter forsuppressing blocking artifacts |
EP1003335A2 (en) * | 1998-11-18 | 2000-05-24 | Tektronix, Inc. | Efficient detection of error blocks in a DCT-based compressed video sequence |
GB2347811A (en) * | 1998-12-24 | 2000-09-13 | Independent Television Commiss | Measuring blockiness in decoded video images |
CN1487749A (zh) * | 2002-07-18 | 2004-04-07 | 视频序列中模糊的测量 | |
WO2004049243A1 (en) * | 2002-11-25 | 2004-06-10 | Sarnoff Corporation | Method and apparatus for measuring quality of compressed video sequences without references |
CN1524386A (zh) * | 2001-07-03 | 2004-08-25 | 皇家菲利浦电子有限公司 | 测量数字视频质量的方法 |
CN1655230A (zh) * | 2005-01-18 | 2005-08-17 | 中国电子科技集团公司第三十研究所 | 客观音质评价中基于噪声掩蔽门限算法的巴克谱失真测度方法 |
CN1723711A (zh) * | 2002-12-10 | 2006-01-18 | 皇家飞利浦电子股份有限公司 | 用于数字视频处理的一元化量度(umdvp) |
CN1761975A (zh) * | 2003-06-18 | 2006-04-19 | 英国电讯有限公司 | 视频质量评估中的边缘分析 |
US7102667B2 (en) * | 2002-03-18 | 2006-09-05 | Tektronix, Inc. | Picture quality diagnostics for revealing cause of perceptible impairments |
WO2006131866A2 (en) * | 2005-06-08 | 2006-12-14 | Koninklijke Philips Electronics N.V. | Method and system for image processing |
WO2007020572A1 (en) * | 2005-08-18 | 2007-02-22 | Koninklijke Philips Electronics N.V. | Image processor comprising a block artifacts detector |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6433891B1 (en) * | 1998-12-14 | 2002-08-13 | Oak Technology, Inc. | Stochastic screening method with dot pattern regularity control and dot growth |
WO2001020912A1 (en) * | 1999-09-14 | 2001-03-22 | Koninklijke Philips Electronics N.V. | Method and device for identifying block artifacts in digital video pictures |
US6437821B1 (en) * | 1999-12-22 | 2002-08-20 | Tektronix, Inc. | Harmonic measurement of blockiness in video signals |
US7110602B2 (en) * | 2002-08-21 | 2006-09-19 | Raytheon Company | System and method for detection of image edges using a polar algorithm process |
US20040175056A1 (en) * | 2003-03-07 | 2004-09-09 | Chulhee Lee | Methods and systems for objective measurement of video quality |
-
2008
- 2008-04-08 US US12/099,763 patent/US8294770B2/en active Active
- 2008-04-08 WO PCT/US2008/059690 patent/WO2008124743A1/en active Application Filing
- 2008-04-08 CN CN2008800192945A patent/CN101682768B/zh not_active Expired - Fee Related
- 2008-04-08 JP JP2010503166A patent/JP5269877B2/ja not_active Expired - Fee Related
- 2008-04-08 EP EP08745323.9A patent/EP2137976B1/en not_active Not-in-force
Patent Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5920356A (en) * | 1995-06-06 | 1999-07-06 | Compressions Labs, Inc. | Coding parameter adaptive transform artifact reduction process |
EP0961229A2 (en) * | 1998-05-29 | 1999-12-01 | STMicroelectronics, Inc. | Non-linear adaptive image filter forsuppressing blocking artifacts |
EP1003335A2 (en) * | 1998-11-18 | 2000-05-24 | Tektronix, Inc. | Efficient detection of error blocks in a DCT-based compressed video sequence |
GB2347811A (en) * | 1998-12-24 | 2000-09-13 | Independent Television Commiss | Measuring blockiness in decoded video images |
CN1524386A (zh) * | 2001-07-03 | 2004-08-25 | 皇家菲利浦电子有限公司 | 测量数字视频质量的方法 |
US7102667B2 (en) * | 2002-03-18 | 2006-09-05 | Tektronix, Inc. | Picture quality diagnostics for revealing cause of perceptible impairments |
CN1487749A (zh) * | 2002-07-18 | 2004-04-07 | 视频序列中模糊的测量 | |
WO2004049243A1 (en) * | 2002-11-25 | 2004-06-10 | Sarnoff Corporation | Method and apparatus for measuring quality of compressed video sequences without references |
CN1723711A (zh) * | 2002-12-10 | 2006-01-18 | 皇家飞利浦电子股份有限公司 | 用于数字视频处理的一元化量度(umdvp) |
CN1761975A (zh) * | 2003-06-18 | 2006-04-19 | 英国电讯有限公司 | 视频质量评估中的边缘分析 |
CN1655230A (zh) * | 2005-01-18 | 2005-08-17 | 中国电子科技集团公司第三十研究所 | 客观音质评价中基于噪声掩蔽门限算法的巴克谱失真测度方法 |
WO2006131866A2 (en) * | 2005-06-08 | 2006-12-14 | Koninklijke Philips Electronics N.V. | Method and system for image processing |
WO2007020572A1 (en) * | 2005-08-18 | 2007-02-22 | Koninklijke Philips Electronics N.V. | Image processor comprising a block artifacts detector |
Also Published As
Publication number | Publication date |
---|---|
EP2137976A1 (en) | 2009-12-30 |
JP2010532935A (ja) | 2010-10-14 |
JP5269877B2 (ja) | 2013-08-21 |
EP2137976B1 (en) | 2017-06-07 |
WO2008124743A1 (en) | 2008-10-16 |
US20080266398A1 (en) | 2008-10-30 |
CN101682768A (zh) | 2010-03-24 |
US8294770B2 (en) | 2012-10-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101682768B (zh) | 用于空间隔离的伪影剖析、分类和测量的***和方法 | |
JP4494649B2 (ja) | 基準映像を用いることなくデジタル映像の品質を推定する方法と装置 | |
Saad et al. | Blind prediction of natural video quality | |
Tan et al. | A multi-metric objective picture-quality measurement model for MPEG video | |
EP1383344B1 (en) | Measurement of blurring in video sequences | |
US6822675B2 (en) | Method of measuring digital video quality | |
KR100647146B1 (ko) | 실시간 인간 시각 체계 동작 모델링 방법 | |
CN101160951B (zh) | 一种多媒体视频通信的质量检测方法 | |
US6704451B1 (en) | Method and arrangement for objective assessment of video quality | |
Ferzli et al. | A no-reference objective image sharpness metric based on just-noticeable blur and probability summation | |
US8036485B2 (en) | Systems and methods for measuring loss of detail in a video codec block | |
US20040175056A1 (en) | Methods and systems for objective measurement of video quality | |
CN107211115A (zh) | 用于色度重构的方法和装置 | |
KR20050116893A (ko) | 패턴 적응형 필터링에 의한 영상신호의 평활화 장치 및 그평활화 방법 | |
Shoham et al. | A novel perceptual image quality measure for block based image compression | |
Joy et al. | RECENT DEVELOPMENTS IN IMAGE QUALITY ASSESSMENT ALGORITHMS: A REVIEW. | |
Farias et al. | Perceptual contributions of blocky, blurry and noisy artifacts to overall annoyance | |
Gunawan et al. | Image quality assessment based on harmonics gain/loss information | |
Punchihewa et al. | Objective quality assessment of coded images: the development of new quality metrics | |
Nadenau et al. | Image-compression-related contrast-masking measurements | |
Lee et al. | New full-reference visual quality assessment based on human visual perception | |
Liu et al. | Issues in the design of a no-reference metric for perceived blur | |
Qadri et al. | Frequency domain blockiness measurement for image quality assessment | |
Kayargadde | Feature extraction for image quality prediction | |
Chilukamari et al. | Investigation of the effectiveness of video quality metrics in video pre-processing |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant | ||
TR01 | Transfer of patent right |
Effective date of registration: 20190916 Address after: oregon Patentee after: Giant Plan Co., Ltd. Address before: oregon Patentee before: Tektronix Inc. |
|
TR01 | Transfer of patent right | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20130710 Termination date: 20190408 |
|
CF01 | Termination of patent right due to non-payment of annual fee |