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公开(公告)号：US20170070718A1
公开(公告)日：2017-03-09
申请号：US14872098
申请日：2015-09-30
Applicant: Apple Inc.
Inventor： Farhan A. Baqai , Fabio Riccardi , Russell A. Pflughaupt , Claus Molgaard , Gijesh Varghese
CPC classification number: H04N9/77 , G06K9/40 , G06T5/002 , G06T5/009 , G06T5/20 , G06T5/50 , G06T2207/10024 , G06T2207/20016 , G06T2207/20182 , G06T2207/20208 , G06T2207/20221 , H04N5/208 , H04N5/217 , H04N9/646 , H04N9/67 , H04N9/69 , H04N9/73
Abstract: Techniques for de-noising a digital image using a multi-band noise filter and a unique combination of texture and chroma metrics are described. A novel texture metric may be used during multi-band filter operations on an image's luma channel to determine if a given pixel is associated with a textured/smooth region of the image. A novel chroma metric may be used during the the same multi-band filter operation to determine if the same pixel is associated with a blue/not-blue region of the image. Pixels identified as being associated with a smooth blue region may be aggressively de-noised and conservatively sharpened. Pixels identified as being associated with a textured blue region may be conservatively de-noised and aggressively sharpened. By coupling texture and chroma constraints it has been shown possible to mitigate noise in an image's smooth blue regions without affecting the edges/texture in other blue objects.
Abstract translation: 描述了使用多频带噪声滤波器去噪数字图像和纹理和色度度量的唯一组合的技术。 在图像的亮度信道的多频带滤波操作期间可以使用新的纹理度量，以确定给定像素是否与图像的纹理/平滑区域相关联。 在相同的多频带滤波器操作期间可以使用新的色度度量以确定相同的像素是否与图像的蓝色/非蓝色区域相关联。 被识别为与平滑蓝色区域相关联的像素可能被积极地去噪和保守地削尖。 识别为与纹理蓝色区域相关联的像素可以被保守地去噪和积极地削尖。 通过耦合纹理和色度约束，已经显示可以减轻图像平滑蓝色区域中的噪声，而不会影响其他蓝色对象中的边缘/纹理。
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公开(公告)号：US20170069060A1
公开(公告)日：2017-03-09
申请号：US14872104
申请日：2015-09-30
Applicant: Apple Inc.
Inventor： Farhan A. Baqai , Fabio Riccardi , Russell A. Pflughaupt , Claus Molgaard , Gijesh Varghese
CPC classification number: H04N9/77 , G06K9/40 , G06T5/002 , G06T5/009 , G06T5/20 , G06T5/50 , G06T2207/10024 , G06T2207/20016 , G06T2207/20182 , G06T2207/20208 , G06T2207/20221 , H04N5/208 , H04N5/217 , H04N9/646 , H04N9/67 , H04N9/69 , H04N9/73
Abstract: Systems, methods, and computer readable media to fuse digital images are described. In general, techniques are disclosed that use multi-band noise reduction techniques to represent input and reference images as pyramids. Once decomposed in this manner, images may be fused using novel low-level (noise dependent) similarity measures. In some implementations similarity measures may be based on intra-level comparisons between reference and input images. In other implementations, similarity measures may be based on inter-level comparisons. In still other implementations, mid-level semantic features such as black-level may be used to inform the similarity measure. In yet other implementations, high-level semantic features such as color or a specified type of region (e.g., moving, stationary, or having a face or other specified shape) may be used to inform the similarity measure.
Abstract translation: 描述了融合数字图像的系统，方法和计算机可读介质。 通常，公开了使用多频带降噪技术将输入和参考图像表示为金字塔的技术。 一旦以这种方式分解，可以使用新颖的低级（噪声依赖）相似性度量来融合图像。 在一些实现中，相似性度量可以基于参考和输入图像之间的层内比较。 在其他实现中，相似性度量可以基于层间比较。 在其他实现中，可以使用诸如黑色级别的中级语义特征来通知相似性度量。 在其他实现中，可以使用诸如颜色或指定类型的区域（例如，移动，静止或具有面部或其他指定形状）的高级语义特征来通知相似性度量。
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公开(公告)号：US09626745B2
公开(公告)日：2017-04-18
申请号：US14872104
申请日：2015-09-30
Applicant: Apple Inc.
Inventor： Farhan A. Baqai , Fabio Riccardi , Russell A. Pflughaupt , Claus Molgaard , Gijesh Varghese
CPC classification number: H04N9/77 , G06K9/40 , G06T5/002 , G06T5/009 , G06T5/20 , G06T5/50 , G06T2207/10024 , G06T2207/20016 , G06T2207/20182 , G06T2207/20208 , G06T2207/20221 , H04N5/208 , H04N5/217 , H04N9/646 , H04N9/67 , H04N9/69 , H04N9/73
Abstract: Systems, methods, and computer readable media to fuse digital images are described. In general, techniques are disclosed that use multi-band noise reduction techniques to represent input and reference images as pyramids. Once decomposed in this manner, images may be fused using novel low-level (noise dependent) similarity measures. In some implementations similarity measures may be based on intra-level comparisons between reference and input images. In other implementations, similarity measures may be based on inter-level comparisons. In still other implementations, mid-level semantic features such as black-level may be used to inform the similarity measure. In yet other implementations, high-level semantic features such as color or a specified type of region (e.g., moving, stationary, or having a face or other specified shape) may be used to inform the similarity measure.
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公开(公告)号：US09641820B2
公开(公告)日：2017-05-02
申请号：US14872098
申请日：2015-09-30
Applicant: Apple Inc.
Inventor： Farhan A. Baqai , Fabio Riccardi , Russell A. Pflughaupt , Claus Molgaard , Gijesh Varghese
CPC classification number: H04N9/77 , G06K9/40 , G06T5/002 , G06T5/009 , G06T5/20 , G06T5/50 , G06T2207/10024 , G06T2207/20016 , G06T2207/20182 , G06T2207/20208 , G06T2207/20221 , H04N5/208 , H04N5/217 , H04N9/646 , H04N9/67 , H04N9/69 , H04N9/73
Abstract: Techniques for de-noising a digital image using a multi-band noise filter and a unique combination of texture and chroma metrics are described. A novel texture metric may be used during multi-band filter operations on an image's luma channel to determine if a given pixel is associated with a textured/smooth region of the image. A novel chroma metric may be used during the same multi-band filter operation to determine if the same pixel is associated with a blue/not-blue region of the image. Pixels identified as being associated with a smooth blue region may be aggressively de-noised and conservatively sharpened. Pixels identified as being associated with a textured blue region may be conservatively de-noised and aggressively sharpened. By coupling texture and chroma constraints it has been shown possible to mitigate noise in an image's smooth blue regions without affecting the edges/texture in other blue objects.
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