77 research outputs found
Dünaamiline kiiruse jaotamine interaktiivses mitmevaatelises video vaatevahetuse ennustamineses
In Interactive Multi-View Video (IMVV), the video has been captured by numbers of
cameras positioned in array and transmitted those camera views to users. The user can
interact with the transmitted video content by choosing viewpoints (views from different
cameras in the array) with the expectation of minimum transmission delay while
changing among various views. View switching delay is one of the primary concern that
is dealt in this thesis work, where the contribution is to minimize the transmission delay
of new view switch frame through a novel process of selection of the predicted view
and compression considering the transmission efficiency. Mainly considered a realtime
IMVV streaming, and the view switch is mapped as discrete Markov chain, where
the transition probability is derived using Zipf distribution, which provides information
regarding view switch prediction. To eliminate Round-Trip Time (RTT) transmission
delay, Quantization Parameters (QP) are adaptively allocated to the remaining redundant
transmitted frames to maintain view switching time minimum, trading off with
the quality of the video till RTT time-span. The experimental results of the proposed
method show superior performance on PSNR and view switching delay for better viewing quality over the existing methods
Graph Spectral Image Processing
Recent advent of graph signal processing (GSP) has spurred intensive studies
of signals that live naturally on irregular data kernels described by graphs
(e.g., social networks, wireless sensor networks). Though a digital image
contains pixels that reside on a regularly sampled 2D grid, if one can design
an appropriate underlying graph connecting pixels with weights that reflect the
image structure, then one can interpret the image (or image patch) as a signal
on a graph, and apply GSP tools for processing and analysis of the signal in
graph spectral domain. In this article, we overview recent graph spectral
techniques in GSP specifically for image / video processing. The topics covered
include image compression, image restoration, image filtering and image
segmentation
Adapting the streaming video based on the estimated motion position
In real time video streaming, the frames must meet their timing constraints, typically specified as their deadlines. Wireless networks may suffer from bandwidth limitations. To reduce the data transmission over the wireless networks, we propose an adaption technique in the server side by extracting a part of the video frames that considered as a Region Of Interest (ROI), and drop the part outside the ROI from the frames that are between reference frames. The estimated position of the selection of the ROI is computed by using the Sum of Squared Differences (SSD) between consecutive frames. The reconstruction mechanism to the region outside the ROI is implemented in the mobile side by using linear interpolation between reference frames. We evaluate the proposed approach by using Mean Opinion Score (MOS) measurements. MOS are used to evaluate two scenarios with equivalent encoding size, where the users observe the first scenario with low bit rate for the original videos, while for the second scenario the users observe our proposed approach with high bit rate. The results show that our technique significantly reduces the amounts of data are streamed over wireless networks, while the reconstruction mechanism will provides acceptable video quality
Light field image coding with flexible viewpoint scalability and random access
This paper proposes a novel light field image compression approach with viewpoint scalability and random access functionalities. Although current state-of-the-art image coding algorithms for light fields already achieve high compression ratios, there is a lack of support for such functionalities, which are important for ensuring compatibility with different displays/capturing devices, enhanced user interaction and low decoding delay. The proposed solution enables various encoding profiles with different flexible viewpoint scalability and random access capabilities, depending on the application scenario. When compared to other state-of-the-art methods, the proposed approach consistently presents higher bitrate savings (44% on average), namely when compared to pseudo-video sequence coding approach based on HEVC. Moreover, the proposed scalable codec also outperforms MuLE and WaSP verification models, achieving average bitrate saving gains of 37% and 47%, respectively. The various flexible encoding profiles proposed add fine control to the image prediction dependencies, which allow to exploit the tradeoff between coding efficiency and the viewpoint random access, consequently, decreasing the maximum random access penalties that range from 0.60 to 0.15, for lenslet and HDCA light fields.info:eu-repo/semantics/acceptedVersio
Optimal coding unit decision for early termination in high efficiency video coding using enhanced whale optimization algorithm
Video compression is an emerging research topic in the field of block based video encoders. Due to the growth of video coding technologies, high efficiency video coding (HEVC) delivers superior coding performance. With the increased encoding complexity, the HEVC enhances the rate-distortion (RD) performance. In the video compression, the out-sized coding units (CUs) have higher encoding complexity. Therefore, the computational encoding cost and complexity remain vital concerns, which need to be considered as an optimization task. In this manuscript, an enhanced whale optimization algorithm (EWOA) is implemented to reduce the computational time and complexity of the HEVC. In the EWOA, a cosine function is incorporated with the controlling parameter A and two correlation factors are included in the WOA for controlling the position of whales and regulating the movement of search mechanism during the optimization and search processes. The bit streams in the Luma-coding tree block are selected using EWOA that defines the CU neighbors and is used in the HEVC. The results indicate that the EWOA achieves best bit rate (BR), time saving, and peak signal to noise ratio (PSNR). The EWOA showed 0.006-0.012 dB higher PSNR than the existing models in the real-time videos
Efficient quantum image representation and compression circuit using zero-discarded state preparation approach
Quantum image computing draws a lot of attention due to storing and
processing image data faster than classical. With increasing the image size,
the number of connections also increases, leading to the circuit complex.
Therefore, efficient quantum image representation and compression issues are
still challenging. The encoding of images for representation and compression in
quantum systems is different from classical ones. In quantum, encoding of
position is more concerned which is the major difference from the classical. In
this paper, a novel zero-discarded state connection novel enhance quantum
representation (ZSCNEQR) approach is introduced to reduce complexity further by
discarding '0' in the location representation information. In the control
operational gate, only input '1' contribute to its output thus, discarding zero
makes the proposed ZSCNEQR circuit more efficient. The proposed ZSCNEQR
approach significantly reduced the required bit for both representation and
compression. The proposed method requires 11.76\% less qubits compared to the
recent existing method. The results show that the proposed approach is highly
effective for representing and compressing images compared to the two relevant
existing methods in terms of rate-distortion performance.Comment: 7 figure
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