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201results about How to "Efficient reconstruction" patented technology

Generation of spatial downmixes from parametric representations of multi channel signals

A headphone down mix signal can be efficiently derived from a parametric down mix of a multi-channel signal, when modified HRTFs (head related transfer functions) are derived from HRTFs of a multi-channel signal using a level parameter having information on a level relation between two channels of the multi-channel signals such that a modified HRTF is stronger influenced by the HRTF of a channel having a higher level than by the HRTF of a channel having a lower level. Modified HRTFs are derived within the decoding process taking into account the relative strength of the channels associated to the HRTFs. The HRTFs are thus modified such that a down mix signal of a parametric representation of a multi-channel signal can directly be used to synthesize the headphone down mix signal without the need of an intermediate full parametric multi-channel reconstruction of the parametric down mix.
Owner:DOLBY INT AB

System and Method for Real-Time Super-Resolution

A method and system are presented for real time Super-Resolution image reconstruction. According to this technique, data indicative of a video frame sequence compressed by motion compensated compression technique is processed, and representations of one or more video objects (VOs) appearing in one or more frames of said video frame sequence are obtained. At least one of these representations is utilized as a reference representation and motion vectors, associating said representations with said at least one reference representation, are obtained from said data indicative of the video frame sequence. The representations and the motion vectors are processed, and pixel displacement maps are generated, each associating at least some pixels of one of the representations with locations on said at least one reference representation. The reference representation is re-sampled according to the sub-pixel accuracy of the displacement maps, and a re-sampled reference representation is obtained. Pixels of said representations are registered against the re-sampled reference representation according to the displacement maps, thereby providing super-resolved image of the reference representation of said one or more VOs.
Owner:RAMOT AT TEL AVIV UNIV LTD

Enhanced Method for Signal Shaping in Multi-Channel Audio Reconstruction

The present invention is based on the finding that a reconstructed output channel, reconstructed with a multi-channel reconstructor using at least one downmix channel derived by downmixing a plurality of original channels and using a parameter representation including additional information on a temporal fine structure of an original channel can be reconstructed efficiently with high quality, when a generator for generating a direct signal component and a diffuse signal component based on the downmix channel is used. The quality can be essentially enhanced, if only the direct signal component is modified such that the temporal fine structure of the reconstructed output channel is fitting a desired temporal fine structure, indicated by the additional information on the temporal fine structure transmitted.
Owner:FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG EV

Video super-resolution reconstruction method based on deep residual network

The invention discloses a video super-resolution reconstruction method based on a deep residual network. According to the method, a corresponding high-resolution image is reconstructed from a set of continuous low-resolution video frame images of a video sequence so that the video display effect can be obviously enhanced. The innovativeness of the video super-resolution algorithm is mainly reflected in two aspects: firstly, the initial stage, the series convolutional layer computation stage and the residual block computation stage are directly performed from the low-resolution video images by using the deep residual network and then the high-resolution video image is reconstructed by using the deconvolution and convolution operation mode gradually so that conventional preprocessing of bicubic interpolation does not need to be performed on the low-resolution video images; and secondly, compared with the most classic single frame and video super-resolution reconstruction method based on deep learning, the high-resolution video image can be effectively reconstructed in different environments under the condition of using few training data, and the video image display effect can be greatly enhanced.
Owner:福建帝视科技集团有限公司

Machine learning based model localization system

A method for deriving an image sensor's 3D pose estimate from a 2D scene image input includes at least one Machine Learning algorithm trained a priori to generate a 3D depth map estimate from the 2D image input, which is used in conjunction with physical attributes of the source imaging device to make an accurate estimate of the imaging device 3D location and orientation relative to the 3D content of the imaged scene. The system may optionally employ additional Machine Learning algorithms to recognize objects within the scene to further infer contextual information about the scene, such as the image sensor pose estimate relative to the floor plane or the gravity vector. The resultant refined imaging device localization data can be applied to static (picture) or dynamic (video), 2D or 3D images, and is useful in many applications, most specifically for the purposes of improving the realism and accuracy of primarily static, but also dynamic Augmented Reality (AR) applications.
Owner:MANOR FINANCIAL INC

Super-resolution imaging system based on compression coding aperture and imaging method thereof

The invention discloses a super-resolution imaging system based on a compression coding aperture and an imaging method thereof, mainly solving a problem of expensive imaging cost in the prior art. The method comprises the following steps: designing a convolution template, and making a coding aperture according to coherence of a light source; placing the prepared coding aperture at a position of aperture diaphragm in an optical system and pressing a shutter for imaging, and obtaining a low resolution coding image; transmitting the coding image to a master control computer, decoding super-resolution to reconstruct a high-resolution image, and using a denoising algorithm to remove an artificial trace in the high-resolution image. The system and the method are characterized in that: restriction of a Nyquist criterion is broken through, low frequency sampling is carried out on a scene, the high-resolution image is obtained through super-resolution reconstruction, data waste caused by first sampling and second compression of a traditional imaging system is overcome, in sampling, data volume is compressed, imaging cost, compression cost and transmission cost are reduced, and the system and the method can be used for infrared imaging and remote sensing imaging technology.
Owner:XIDIAN UNIV

Non local joint sparse representation based hyperspectral image super-resolution reconstruction method

The invention relates to a non local joint sparse representation based hyperspectral image super-resolution reconstruction method. The method comprises: firstly, performing dictionary training on a low-spatial-resolution hyperspectral image with an online dictionary training method to obtain a corresponding spectral dictionary; secondly, performing joint sparse representation on similar pixel vectors by virtue of a full-color image of a same scene, and reconstructing a high-resolution image; and finally, processing the reconstructed high-resolution image by utilizing an iterative reverse projection technology to obtain a high-resolution hyperspectral image with smaller reconstruction error and higher visual quality. According to the method, the similar pixel vectors are subjected to non local joint sparse representation by utilizing the non local self-similarity property of the image, so that the visual quality of the reconstructed image is improved and structural features of edges, textures and the like of the image are reconstructed more effectively in an empty region while image spectral information is kept complete; and multiple wavebands of the hyperspectral image are subjected to sparse representation and reconstruction at the same time, so that the hyperspectral image with relatively high definition and identification degree can be reconstructed.
Owner:西安晨帆智能科技有限公司

Mobile laser measurement point-based indoor structured three-dimensional reconstruction method

The invention discloses a mobile laser measurement point-based indoor structured three-dimensional reconstruction method. The mobile laser measurement point-based indoor structured three-dimensional reconstruction method comprises performing room division on the basis of a laser scanning point cloud evidence raster map; performing space division on the basis of vector wall projection line segments; structuring a vector room plan and an indoor three-dimensional model on the basis of vector-raster overlaying. The mobile laser measurement point-based indoor structured three-dimensional reconstruction method makes full use of semantic information and structured elements of indoor space, converts an indoor three-dimensional reconstruction problem into room division and GIS-based (geographic information system-based) overlaid analysis problems, takes divided rooms as prior knowledge to solve the problem of shading and in complete data of laser measurement during a modeling process and can rapidly and effectively structure an indoor building three-dimensional model with topological consistency. Compared with other methods, the mobile laser measurement point-based indoor structured three-dimensional reconstruction method can better process point cloud data of indoor complicated environment and meet the demands on indoor structuralized three-dimensional reconstruction.
Owner:WUHAN UNIV
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