506 research outputs found
A low-complexity and efficient encoder rate control solution for distributed residual video coding.
Existing encoder rate control (ERC) solutions have two technical limitations that prevent them from being widely used in real-world applications. One is that encoder side information (ESI) is required to be generated which increases the complexity at the encoder. The other is that rate estimation is performed at bit plane level which incurs computation overheads and latency when many bit planes exist. To achieve a low-complexity encoder, we propose a new ERC solution that combines an efficient encoder block mode decision (EBMD) for the distributed residual video coding (DRVC). The main contributions of this paper are as follows: 1) ESI is not required as our ERC is based on the analysis of the statistical characteristics of the decoder side information (DSI); 2) a simple EBMD is introduced which only employs the values of residual pixels at the encoder to classify blocks into Intra mode, Skip mode, and WZ mode; 3) an ERC solution using pseudo-random sequence scrambling is proposed to estimate rates for all WZ blocks at frame level instead of at bit plane level, i.e., only one rate is estimated; and 4) a quantization-index estimation algorithm (QIEA) is proposed to solve the problem of rate underestimation. The simulation results show that the proposed solution is not only low complex but also efficient in both the block mode decision and the rate estimation. Also, as compared to DISCOVER system and the state-of-the-art ERC solution, our solution demonstrates a competitive rate-distortion(RD)performance. Due to maintain the low-complexity nature of the encoder and have good RD performance, we believe that our ERC solution is promising in practice
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
The recently developed Distributed Video Coding (DVC) is typically suitable for the
applications where the conventional video coding is not feasible because of its
inherent high-complexity encoding. Examples include video surveillance usmg
wireless/wired video sensor network and applications using mobile cameras etc. With
DVC, the complexity is shifted from the encoder to the decoder.
The practical application of DVC is referred to as Wyner-Ziv video coding (WZ)
where an estimate of the original frame called "side information" is generated using
motion compensation at the decoder. The compression is achieved by sending only
that extra information that is needed to correct this estimation. An error-correcting
code is used with the assumption that the estimate is a noisy version of the original
frame and the rate needed is certain amount of the parity bits. The side information is
assumed to have become available at the decoder through a virtual channel. Due to
the limitation of compensation method, the predicted frame, or the side information, is
expected to have varying degrees of success. These limitations stem from locationspecific
non-stationary estimation noise. In order to avoid these, the conventional
video coders, like MPEG, make use of frame partitioning to allocate optimum coder
for each partition and hence achieve better rate-distortion performance. The same,
however, has not been used in DVC as it increases the encoder complexity.
This work proposes partitioning the considered frame into many coding units
(region) where each unit is encoded differently. This partitioning is, however, done at
the decoder while generating the side-information and the region map is sent over to
encoder at very little rate penalty. The partitioning allows allocation of appropriate
DVC coding parameters (virtual channel, rate, and quantizer) to each region. The
resulting regions map is compressed by employing quadtree algorithm and
communicated to the encoder via the feedback channel. The rate control in DVC is
performed by channel coding techniques (turbo codes, LDPC, etc.). The performance
of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and
an adaptive WZ DVC is designed both in transform domain and in pixel domain. The
transform domain WZ video coding (TDWZ) has distinct superior performance as
compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the
'
spatial redundancy during the encoding. The performance evaluations show that the
proposed system is superior to the existing distributed video coding solutions.
Although the, proposed system requires extra bits representing the "regions map" to be
transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art
frame based DVC by 0.6-1.9 dB.
The feedback channel (FC) has the role to adapt the bit rate to the changing
'
statistics between the side infonmation and the frame to be encoded. In the
unidirectional scenario, the encoder must perform the rate control. To correctly
estimate the rate, the encoder must calculate typical side information. However, the
rate cannot be exactly calculated at the encoder, instead it can only be estimated. This
work also prbposes a feedback-free region-based adaptive DVC solution in pixel
domain based on machine learning approach to estimate the side information.
Although the performance evaluations show rate-penalty but it is acceptable
considering the simplicity of the proposed algorithm.
vii
Distortion-constraint compression of three-dimensional CLSM images using image pyramid and vector quantization
The confocal microscopy imaging techniques, which allow optical sectioning, have
been successfully exploited in biomedical studies. Biomedical scientists can benefit
from more realistic visualization and much more accurate diagnosis by processing and
analysing on a three-dimensional image data. The lack of efficient image compression
standards makes such large volumetric image data slow to transfer over limited
bandwidth networks. It also imposes large storage space requirements and high cost in
archiving and maintenance.
Conventional two-dimensional image coders do not take into account inter-frame
correlations in three-dimensional image data. The standard multi-frame coders, like
video coders, although they have good performance in capturing motion information,
are not efficiently designed for coding multiple frames representing a stack of optical
planes of a real object. Therefore a real three-dimensional image compression
approach should be investigated.
Moreover the reconstructed image quality is a very important concern in compressing
medical images, because it could be directly related to the diagnosis accuracy. Most of
the state-of-the-arts methods are based on transform coding, for instance JPEG is based on discrete-cosine-transform CDCT) and JPEG2000 is based on discrete-
wavelet-transform (DWT). However in DCT and DWT methods, the control
of the reconstructed image quality is inconvenient, involving considerable costs in
computation, since they are fundamentally rate-parameterized methods rather than
distortion-parameterized methods. Therefore it is very desirable to develop a
transform-based distortion-parameterized compression method, which is expected to
have high coding performance and also able to conveniently and accurately control
the final distortion according to the user specified quality requirement.
This thesis describes our work in developing a distortion-constraint three-dimensional
image compression approach, using vector quantization techniques combined with
image pyramid structures. We are expecting our method to have:
1. High coding performance in compressing three-dimensional microscopic
image data, compared to the state-of-the-art three-dimensional image coders
and other standardized two-dimensional image coders and video coders.
2. Distortion-control capability, which is a very desirable feature in medical 2. Distortion-control capability, which is a very desirable feature in medical
image compression applications, is superior to the rate-parameterized methods
in achieving a user specified quality requirement.
The result is a three-dimensional image compression method, which has outstanding
compression performance, measured objectively, for volumetric microscopic images.
The distortion-constraint feature, by which users can expect to achieve a target image
quality rather than the compressed file size, offers more flexible control of the
reconstructed image quality than its rate-constraint counterparts in medical image
applications. Additionally, it effectively reduces the artifacts presented in other
approaches at low bit rates and also attenuates noise in the pre-compressed images.
Furthermore, its advantages in progressive transmission and fast decoding make it
suitable for bandwidth limited tele-communications and web-based image browsing
applications
Progressive transmission of medical images
A novel adaptive source-channel coding scheme for progressive transmission of medical images with a feedback system is therefore proposed in this dissertation. The overall design includes Discrete Wavelet Transform (DWT), Embedded Zerotree Wavelet (EZW) coding, Joint Source-Channel Coding (JSCC), prioritization of region of interest (RoI), variability of parity length based on feedback, and the corresponding hardware design utilising Simulink. The JSCC can achieve an efficient transmission by incorporating unequal error projection (UEP) and rate allocation. An algorithm is also developed to estimate the number of erroneous data in the receiver. The algorithm detects the address in which the number of symbols for each subblock is indicated, and reassigns an estimated correct data according to a decision making criterion, if error data is detected. The proposed system has been designed based on Simulink which can be used to generate netlist for portable devices. A new compression method called Compressive Sensing (CS) is also revisited in this work. CS exhibits many advantages in comparison with EZW based on our experimental results. DICOM JPEG2000 is an efficient coding standard for lossy or lossless multi-component image coding. However, it does not provide any mechanism for automatic RoI definition, and is more complex compared to our proposed scheme. The proposed system significantly reduces the transmission time, lowers computation cost, and maintains an error-free state in the RoI with regards to the above provided features. A MATLAB-based TCP/IP connection is established to demonstrate the efficacy of the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary and symmetric channel (BSC) and Rayleigh channel. The experimental results confirm the effectiveness of the design.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Constant-SNR, rate control and entropy coding for predictive lossy hyperspectral image compression
Predictive lossy compression has been shown to represent a very flexible framework for lossless and lossy onboard compression of multispectral and hyperspectral images with quality and rate control. In this paper, we improve predictive lossy compression in several ways, using a standard issued by the Consultative Committee on Space Data Systems, namely CCSDS-123, as an example of application. First, exploiting the flexibility in the error control process, we propose a constant-signal-to-noise-ratio algorithm that bounds the maximum relative error between each pixel of the reconstructed image and the corresponding pixel of the original image. This is very useful to avoid low-energy areas of the image being affected by large errors. Second, we propose a new rate control algorithm that has very low complexity and provides performance equal to or better than existing work. Third, we investigate several entropy coding schemes that can speed up the hardware implementation of the algorithm and, at the same time, improve coding efficiency. These advances make predictive lossy compression an extremely appealing framework for onboard systems due to its simplicity, flexibility, and coding efficiency
Advanced distributed video coding techniques
EThOS - Electronic Theses Online ServiceGBUnited Kingdo
- …