scispace - formally typeset
Search or ask a question
Topic

Inter frame

About: Inter frame is a research topic. Over the lifetime, 4154 publications have been published within this topic receiving 63549 citations.


Papers
More filters
Patent
18 Mar 2015
TL;DR: In this article, the quality of static image frames having a relatively long residence time in a frame buffer on a sink device is improved by encoding additional information to improve the representation of the now static frame.
Abstract: One or more system, apparatus, method, and computer readable media is described for improving the quality of static image frames having a relatively long residence time in a frame buffer on a sink device. Where a compressed data channel links a source and sink, the source may encode additional frame data to improve the quality of a static frame presented by a sink display. A display source may encode frame data at a nominal quality and transmit a packetized stream of the compressed frame data. In the absence of a timely frame buffer update, the display source encodes additional information to improve the image quality of the representation of the now static frame. A display sink device presents a first representation of the frame at the nominal image quality, and presents a second representation of the frame at the improved image quality upon subsequently receiving the frame quality improvement data.

16 citations

Journal ArticleDOI
TL;DR: In this paper, a scheme for interframe nonlinear adaptive prediction is proposed, where a quadratic operator, adapted pixel-by-pixel by an LMS technique, proves to be able to outperform conventional predictors when motion is present in the scene.
Abstract: A scheme for interframe nonlinear adaptive prediction is proposed. A quadratic operator, adapted pixel-by-pixel by an LMS technique, proves to be able to outperform conventional predictors when motion is present in the scene.

16 citations

Patent
10 Jul 2002
TL;DR: In this paper, the authors proposed a method to divide the motion image into groups as per the step length M, and then carry out W-quatrature converting to M frame image in each group to obtain the new M-frame image, and carry out the target bit distribution according to the compressing ratio requirement and the different importance of M frame new image.
Abstract: A compressing or decompressing method used for motion image (digital video frequency) data utilizes w-quatrature converting to process several continuous frame in image series on the time axis to eliminate the interframe information redundancy. The present invention includes the steps as follows: to divide the motion image into groups as per the step length M, to carry out W-quatrature convertingto M frame image in each group to obtain the new M frame image, to carry out the target bit distribution according to the compressing ratio requirement and the different importance of M frame new image and to carry out coding for M frame new frame separately. The invented iinterframe processing method is very simple in calculation which is able to realize the real time compressing by the softwareor is realized by hardware for lower cost and more quick calculation.

16 citations

Patent
06 Apr 2016
TL;DR: In this paper, the authors proposed an inter-frame noise reduction method based on motion detection, where moving targets are extracted by a multi-Gaussian mixture background model method and an overlapping stationary area between two adjacent frames are found, then interframe accumulative filtering is performed on the area, and moving target areas and non-moving target areas in non-overlapping areas are replaced by background models established by an intra-frame filtering algorithm and the multiscale mixture background models method respectively.
Abstract: The invention discloses an inter-frame noise reduction method based on motion detection According to the method, moving targets are extracted by a multi-Gaussian mixture background model method and an overlapping stationary area between two adjacent frames are found, then inter-frame accumulative filtering is performed on the area, and moving target areas and non-moving target areas in non-overlapping areas are replaced by background models established by an intra-frame filtering algorithm and the multi-Gaussian mixture background model method respectively Meanwhile, the algorithm can also self-adaptively adjust the number of stack frames and has a multistage adjustable function The innovative points reside in that moving target detection of images is performed firstly, then AND operation is performed on two successive frames of foreground images including the moving targets only, and the inter-frame filtering algorithm, the intra-frame filtering algorithm or a background model replacement algorithm is selected according to the result of AND operation so that the phenomena of edge virtual images, pseudo images and even lost of the moving targets caused by the conventional inter-frame filtering algorithm can be avoided, and the great noise reduction effect of the moving images can also be achieved

16 citations

Proceedings ArticleDOI
Bo Yan1, H. Gharavi
12 Dec 2008
TL;DR: A new hybrid motion vector extrapolation (HMVE) algorithm is proposed to recover the whole missing frame and is capable of estimating the missing motion vectors with much greater accuracy than other existing methods.
Abstract: For low bitrate video communications, each video frame usually fills the payload of a single network packet. In this situation, the loss of a packet may result in loosing the entire video frame. Currently, most existing error concealment algorithms can only deal with the loss of macroblocks and are not able to conceal the whole missing frame. In this paper, we have proposed a new hybrid motion vector extrapolation (HMVE) algorithm to recover the whole missing frame. The proposed algorithm is capable of estimating the missing motion vectors with much greater accuracy than other existing methods. Experimental results show that it is highly effective and significantly outperforms other existing frame recovery methods.

16 citations


Network Information
Related Topics (5)
Feature (computer vision)
128.2K papers, 1.7M citations
86% related
Feature extraction
111.8K papers, 2.1M citations
86% related
Image segmentation
79.6K papers, 1.8M citations
86% related
Convolutional neural network
74.7K papers, 2M citations
83% related
Image processing
229.9K papers, 3.5M citations
82% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202324
202272
202162
202084
2019110
201897