220 results about "Temporal filter" patented technology

An efficient and non-iterative 3D post processing method and system is proposed for mosquito noise reduction, block localization and correction in DCT block-based decoded images. The 3D post processing is based on a simple classification that segments a picture in multiple regions such as Edge, Near Edge, Flat, Near Flat and Texture regions. The proposed technique comprises also an efficient and shape adaptive local power estimation for equivalent additive noise and provides simple noise power weighting for each above cited region. Temporal filtering configurations using Minimum Noise Variance Criterion are proposed for reducing temporally varying coding artifacts. A Minimum Mean Square Error or Minimum Mean Square Error-like noise reduction with robust and effective shape adaptive windowing is utilized for smoothing mosquito and/or random noise for the whole image, particularly for Edge regions. The proposed technique comprises also signal domain histogram analysis based Block Localization and adaptive edge based Block artifact correction. Finally, is also proposed an optional adaptive detail enhancer which can enhances the luminance signal in eight directions differently.

A non-iterative 3D processing method and system is disclosed for generic noise reduction. The 3D noise reducer is based on a simple conversion of the five types of noise to equivalent additive noise of varying statistics. The proposed technique comprises also an efficient temporal filtering technique which combines Minimization of Output Noise Variance (MNV) and Embedded Motion Estimation (EME). The proposed temporal filtering technique may be furthermore combined with classical motion estimation and motion compensation for more efficient noise reducer. The proposed technique comprises also a spatial noise reducer which combines Minimum Mean Squared Error (MMSE) with robust and effective shape adaptive windowing (SAW) is utilized for smoothing random noise in the whole image, particularly for edge regions. Another modification to MMSE is also introduced for handling banding effect for eventual excessive filtering in slowly varying regions.

Provided is a method of removing noise from digital moving picture data reducing the number of frames used in a temporal filtering operation and able to detect motion between frames easily. The method comprises a method of spatial filtering, a method of temporal filtering, and a method of performing the spatial filtering and the temporal filtering sequentially. The spatial filtering method applies a spatial filtering in a YCbCr color space, preserving a contour/edge in the image in the spatial domain, and generating a weight that is adaptive to the noise for discriminating the contour/edge in the temporal filtering operation. The temporal filtering method applies temporal filtering based on motion detection and scene change detection, compensating for global motion, the motion detection considering the brightness difference and color difference of the pixels compared between frames in the temporal filtering operation, and a weight that is adaptive to the noise for detecting the motion in the temporal filtering operation. The spatial filtering method is preferably performed first, and the temporal filtering method is performed with the result of the spatial filtering.

A method and apparatus for motion blur and ghosting prevention in imaging system is presented. A residue image is computed by performing spatial-temporal filter with a set of absolute image difference of image pairs from input images. A noise adaptive pixel threshold is computed for every pixel based on noise statistics of image sensor. The residue image and the noise adaptive pixel threshold are used to create a motion masking map. The motion masking map is used to represent motion and non-motion pixels in pixels merging. The pixels merging step is performed to generate an output image by considering the motion pixels where the motion pixels are performed separately. The resulting output image having no or less motion blur and ghosting artifacts can be obtained, even the input images having different degree of motion blur between each of the image, while the complexity is low. It is preferred that the current invention is applied in the Bayer raw domain. The benefit is reduced computation and memory because only 1 color component is processed for each pixel. Another benefit is higher signal fidelity because processing in the Bayer raw domain is unaffected by demosaicing artifacts, especially along edges. However, the current invention can also be applied in RGB domain.

A video noise reduction system for a set of video frames that computes a first motion signal using a current frame and multiple consecutive previous frames, computes a second motion signal using the current frame and the processed preceding frame; computes the multi-frame temporal average of the current frame and multiple consecutive previous frames; computes the recursive average of the current frame and the processed preceding frame; generates a temporal filtered signal by soft switching between the multi-frame temporal average and the recursive average based on the first motion signal; applies a spatial filter to the current frame to generate a spatial filtered signal; and combines the temporal filtered signal and the spatial filtered signal based on the second motion signal to generate a final noise reduced video output signal.

Techniques for deriving a provenance of one or more of a plurality of output data elements generated from a given output port of a PC are provided. At least one dependency function is created that relates the one or more output data elements to a set of one or more input ports of the PC and a corresponding plurality of input data elements. The dependency function comprises an encoding of at least one of one or more temporal filters and one or more sequence filters relating to the plurality of input data elements. The at least one dependency function is stored. A history of stream-level bindings of one or more input streams to one or more input ports of the processing component and one or more output streams from one or more output ports of the processing component is stored. The plurality of input data elements belonging to the one or more input streams and the plurality of output data elements belonging to the one or more output streams are stored. The set of one or more input data elements from the plurality of input data elements are determined that relate to the one or more output data elements in accordance with at least one dependency function and the history of stream-level bindings.

A method for encoding video signals by inverse motion compensated temporal filtering where video frames of a base layer are used to encode video frames of an enhanced layer into predicted images. For each image block in an arbitrary frame in an enhanced layer frame sequence, an area including a block, which is present in a base layer frame temporally coincident with the arbitrary frame and is at the same position as the image block, is enlarged according to the ratio between screen sizes of the two layers. A reference block most highly correlated with the image block is searched for in the enlarged area in the temporally coincident base layer frame through motion estimation and is used to obtain pixel difference values and a motion vector of the image block for encoding the image block into a predicted image, thereby improving coding efficiency.

Scalable video coding and decoding methods, a scalable video encoder, and a scalable video decoder. The scalable video coding method includes receiving a GOP, performing temporal filtering and spatial transformation thereon, quantizing and generating a bitstream. The scalable video encoder for performing the scalable video coding method includes a weight determination block which determines a weight for scaling. The scalable video decoding method includes dequantizing the coded image information obtained from a received bitstream, performing descaling, inverse spatial transformation, and inverse temporal filtering on the scaled transform coefficients, thereby recovering video frames. The scalable video decoder for performing the scalable video decoding method includes an inverse weighting block. The standard deviation of Peak Signal to Noise Ratios (PSNRs) of frames included in a group of pictures (GOP) is reduced so that video coding performance can be increased.

A process and methods of digital enhancement of motion pictures and other moving image sequences for the purpose of being exhibited in an alternative display format including a large format cinema are disclosed. The invention efficiently enhances image resolution and quality through a temporal filtering process and achieves high performance using automated or interactive statistical quality evaluation methods. A system specially designed for efficient temporal computing with a parallel and distributed computing configuration equipped with a variety of optimization schemes is also disclosed. The performance of the process and the system is optimized through an intelligent controller and is scalable to support any throughput requirements demanded for concurrent motion picture releases in the original format as well as in any alternative format.

A motion-adaptive temporal noise reducing method and system for reducing noise in a sequence of video frames is provided. Temporal noise reduction is applied to two video frames, wherein one video frame is the current input noisy frame, and the other video frame is a previous filtered frame stored in memory. Once the current frame is filtered, it is saved into memory for filtering the next incoming frame. A motion-adaptive temporal filtering method is applied for noise reduction. Pixel-wise motion information between the current frame and the previous (filtered) frame in memory is examined. Then the pixels in the current frame are classified into motion region and non-motion region relative to the previous (filtered) frame. In a non-motion region, pixels in the current frame are filtered along the temporal axis. In a motion region, the temporal filter is switched off to avoid motion blurring.

A video decoder comprising (i) a post-processing filter block, (ii) a comfort noise addition block and (iii) a video value/range adjustment block, where the comfort noise addition block is integrated into a video output path of the video decoder. The post-processing filter block may be configured to perform one or more of noise reduction, spatial filtering and temporal filtering on luminance data. The comfort noise addition block may be configured to add comfort noise to the luminance data. The video value/range adjustment block may be configured to adjust one or both of a value and a range of the luminance data.

A system, apparatus, computer readable media, and method are disclosed for generating analytics on customers of service provider merchants. In an example, a transaction record associated with an account identifier of a customer that purchased a first service from a first merchant may be processed and a service date for the first service may be determined. Other transaction records comprising the account identifier and that satisfy a temporal filter may be identified. Each of the other transaction records may include transaction data associated with at least one of: (1) purchase of another service to be provided within a first predetermined amount of time of the service date, and (2) purchase of a product within a second predetermined amount of time of the service date. A spending profile including information on the first service, the service date, and the transaction data for each of the other transaction records may be generated.

Apparatus and methods of motion detection for mosquito noise reduction in video sequences are provided. In one aspect, a method of motion detection in a sequence of digital images classifies a pixel of a plurality of pixels of a current image frame represented by a digital video input signal as a motion or non-motion pixel. A motion value for the pixel is calculated based on the classification of the pixel. The motion value is mapped to a coefficient of a temporal filter based on a control curve. A digital video output signal is generated based on the coefficient.

An adaptive spatio-temporal filter for use in video quality of service instruments based on human vision system models has a pair of parallel, lowpass, spatio-temporal filters receiving a common video input signal. The outputs from the pair of lowpass spatio-temporal filters are differenced to produce the output of the adaptive spatio-temporal filter, with the bandwidths of the pair being such as to produce an overall bandpass response. A filter adaptation controller generates adaptive filter coefficients for each pixel processed based on a perceptual parameter, such as the local average luminance, contrast, etc., of either the input video signal or the output of one of the pair of lowpass spatio-temporal filters. Each of the pair of lowpass spatio-temporal filters has a temporal IIR filter in cascade with a 2-D spatial IIR filter, and each individual filter is composed of a common building block,5 i.e., a first order, unity DC gain, tunable lowpass filter having a topology suitable for IC implementation. At least two of the building blocks make up each filter with the overall adaptive spatio-temporal filter response having a linear portion and a non-linear portion, the linear portion being dominant at low luminance levels and the non-linear portion being consistent with enhanced perceived brightness as the luminance level increases.

A method and apparatus for scalable encoding providing scalability in an encoder. The scalable video encoding apparatus includes a mode selector that determines a temporal filtering order of a frame and a predetermined time limit as a condition for determining to which frame temporal filtering is to be performed, and a temporal filter which performs motion compensation and temporal filtering, according to the temporal filtering order determined in the mode selector, on frames that satisfy the above-described condition. According to the method and apparatus, since scalability is provided in the encoder, stability in the operation of real-time, bidirectional video streaming applications, such as video conferencing, can be ensured.

The invention discloses a P300 signal detection method based on an LSTM network. The method comprises the following steps: step one, an experiment is carried out by using a P300 character speller andEEG signals are extracted to form a training set and a testing set; step two, preprocessing is carried out on the collected data and the processed data are used as an input data set of a model; step three, an LSTM layer is designed as a spatio-temporal filter of the EEG data set, an all-connection layer is added after a least time step of the LSTM layer, a Softmax layer is added to convert a network output value into a probability form, and then the network is trained and a model parameter is determined, wherein the Softmax layer is a generalized form of the logic function; and step four, a model evaluation index and a testing set character recognition rate are calculate to verify the performance of the model. The method has the following characteristics: no manual feature extraction is needed; the recognition performance is good; the generalization ability is high; and the good information conversion rate is realized. The P300 signal detection method is a good P300 classification algorithm.

A video filter includes a motion detector to detect motion between frames of a video for each pixel, a shape adaptive spatial filter and a weighted temporal filter. The spatial filter and the temporal filter are smoothly mixed together based on the amount of motion detected by the motion detector for each pixel. When the motion detected by the motion detector is low, the video filter tends to do more temporal filtering. When the motion detected by the motion detector is high, the video filter tends to do more spatial filtering.

There are provided methods and apparatus for edge-based spatio-temporal filtering. An apparatus for filtering a sequence of pictures includes a spatial filter, a motion compensator, a deblocking filter, and a temporal filter. The spatial filter is for spatially filtering a picture in the sequence and at least one reference picture selected from among previous pictures and subsequent pictures in the sequence with respect to the picture. The motion compensator, in signal communication with the spatial filter, is for forming, subsequent to spatial filtering, multiple temporal predictions for the picture from the at least one reference picture. The deblocking filter, in signal communication with the motion compensator, is for deblock filtering the multiple temporal predictions. The temporal filter, in signal communication with the deblocking filter, is for temporally filtering the multiple temporal predictions and combining the multiple temporal predictions to generate a noise reduced version of the picture.

Certain aspects of a method and system for adaptive preprocessing for an encoder may comprise filtering received video data using one or more spatial and/or temporal filtering parameters. The spatial and/or temporal filtering parameters may be adaptively updated to achieve a targeted bitrate based on statistical analysis of received video data and encoder feedback. The statistical analysis of received video data may comprise analysis of statistical inputs such as an encoding standard of the received video data, an average quantization factor, an input noise level, an average picture luma level, a motion vectors histogram, and a content type detection of the received video data. The spatial filtering parameters may be adaptively updated during an I frame of the received video data and the temporal filtering parameters may be adaptively updated per frame of the received video data.